papers

2021 (20)

D V Litovkin, A V Anikin, O A Sychev, T Petrova (feb 2021) ORM Diagram as an Intermediate Model for OWL Ontology Engineering: Protégé ORM Plugin Implementation. Journal of Physics: Conference Series 1801 (1) pp. 012009. IOP Publishing. doi web bibtex

@article{Litovkin_2021,
	doi = {10.1088/1742-6596/1801/1/012009},
	url = {https://doi.org/10.1088/1742-6596/1801/1/012009},
	year = 2021,
	month = {feb},
	publisher = {{IOP} Publishing},
	volume = {1801},
	number = {1},
	pages = {012009},
	author = {D V Litovkin and A V Anikin and O A Sychev and T Petrova},
	title = {{ORM} Diagram as an Intermediate Model for {OWL} Ontology Engineering: Prot{\'{e}}g{\'{e}} {ORM} Plugin Implementation},
	journal = {Journal of Physics: Conference Series},
	abstract = {OWL2, a widely-used ontology-representation language, is poorly perceived by humans because OWL2 statements have a low level of abstraction. To solve this issue, various OWL2 ontology editors are used, which allow to group statements and represent them using some visual notation. ORM-diagram is a good candidate for an intermediate model for authoring and understanding of OWL2-ontology as Object-Role Modelling notation supports visually distinguishable constructs, has the high expressive capabilities, and implements the node-link paradigm and the attribute-free approach A Protégé plugin allowing to create an ORM2-diagram using the live error checking approach was implemented. The plugin allows us to form a valid object-oriented diagram model in computer memory using a widely known ontology authoring tool Protégé.},
thanks = {rfbr-18-07-00032, rfbr-20-07-00764}
}

Abstract OWL2, a widely-used ontology-representation language, is poorly perceived by humans because OWL2 statements have a low level of abstraction. To solve this issue, various OWL2 ontology editors are used, which allow to group statements and represent them using some visual notation. ORM-diagram is a good candidate for an intermediate model for authoring and understanding of OWL2-ontology as Object-Role Modelling notation supports visually distinguishable constructs, has the high expressive capabilities, and implements the node-link paradigm and the attribute-free approach A Protégé plugin allowing to create an ORM2-diagram using the live error checking approach was implemented. The plugin allows us to form a valid object-oriented diagram model in computer memory using a widely known ontology authoring tool Protégé.

O. Sychev (2021) Combining neural networks and symbolic inference in a hybrid cognitive architecture. Procedia Computer Science 190 pp. 728-734. Elsevier B.V.. doi web bibtex

@CONFERENCE{Sychev2021728,
author={Sychev, O.},
title={Combining neural networks and symbolic inference in a hybrid cognitive architecture},
journal={Procedia Computer Science},
year={2021},
volume={190},
pages={728-734},
doi={10.1016/j.procs.2021.06.085},
url={https://www.sciencedirect.com/science/article/pii/S1877050921013405?via%3Dihub},
affiliation={Volgograd State Technical University, Lenin Ave, 28, Volgograd, 400005, Russian Federation},
abstract={Recently, there has been a big progress in developing artificial deep-learning neural networks and large-scale knowledge graphs. However, the results in these two research fields have serious drawbacks. The solutions offered by neural networks remain unstable and prone to adversarial attacks: while the percentage of correct answers increases, the incorrect answers often contain glaring errors. Large knowledge graphs contain a lot of facts but little knowledge; they are mostly used for information search and retrieval. The ability to reason conclusions on them is limited, and the majority of modern research turns to approximate methods like neural networks and graph embeddings to draw conclusions and use the accumulated knowledge. In this work, I propose a hybrid cognitive architecture inspired by the observable features of human thinking. Pruning obviously wrong solutions seems to be more natural for human symbolic reasoning than making far-fetched strict logical conclusions, while generating new ideas is often intuitive. So a hybrid cognitive architecture can employ generative neural networks as a sort of "intuition" (generating possible solutions) and symbolic inference as a control contour to verify and filter the generated solutions, weeding out dangerous and wrong ideas. This requires creating knowledge graphs containing negative information: the information of what cannot happen or should not be done and why. The problems of creating negative knowledge graphs are discussed. Hybrid cognitive systems using the proposed architecture will be a lot more trustworthy as they will have a system of human-verifiable rules that ensures avoiding the worst errors which can be used in many fields from decision making to natural-language parsing. © 2020 Elsevier B.V.. All rights reserved.},
correspondence_address1={Sychev, O.; Volgograd State Technical University, Lenin Ave, 28, Russian Federation; эл. почта: oasychev@gmail.com},
publisher={Elsevier B.V.},
issn={18770509},
language={English},
abbrev_source_title={Procedia Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract Recently, there has been a big progress in developing artificial deep-learning neural networks and large-scale knowledge graphs. However, the results in these two research fields have serious drawbacks. The solutions offered by neural networks remain unstable and prone to adversarial attacks: while the percentage of correct answers increases, the incorrect answers often contain glaring errors. Large knowledge graphs contain a lot of facts but little knowledge; they are mostly used for information search and retrieval. The ability to reason conclusions on them is limited, and the majority of modern research turns to approximate methods like neural networks and graph embeddings to draw conclusions and use the accumulated knowledge. In this work, I propose a hybrid cognitive architecture inspired by the observable features of human thinking. Pruning obviously wrong solutions seems to be more natural for human symbolic reasoning than making far-fetched strict logical conclusions, while generating new ideas is often intuitive. So a hybrid cognitive architecture can employ generative neural networks as a sort of “intuition” (generating possible solutions) and symbolic inference as a control contour to verify and filter the generated solutions, weeding out dangerous and wrong ideas. This requires creating knowledge graphs containing negative information: the information of what cannot happen or should not be done and why. The problems of creating negative knowledge graphs are discussed. Hybrid cognitive systems using the proposed architecture will be a lot more trustworthy as they will have a system of human-verifiable rules that ensures avoiding the worst errors which can be used in many fields from decision making to natural-language parsing. © 2020 Elsevier B.V.. All rights reserved.

Oleg Sychev, Mikhail Denisov, Anton Anikin (2021) Ways To Write Algorithms And Their Execution Traces For Teaching Programming. In EpSBS - Volume 102 - NININS 2020. pp. 1029-1039. European Publisher. doi web bibtex

@inproceedings{13164,
    author       = {Oleg Sychev and Mikhail Denisov and Anton Anikin},
    title        = {Ways To Write Algorithms And Their Execution Traces For Teaching Programming},
    booktitle    = {EpSBS - Volume 102 - NININS 2020},
    year         = {2021},
    pages        = {1029-1039},
    publisher    = {European Publisher},
    doi          = {10.15405/epsbs.2021.02.02.127},
    url          = {https://doi.org/10.15405/epsbs.2021.02.02.127},
    thanks = {rfbr-20-07-00764}
}

Oleg Sychev, Anton Anikin, Nikita Penskoy, Mikhail Denisov, Artem Prokudin (2021) CompPrehension - Model-Based Intelligent Tutoring System on Comprehension Level. In Intelligent Tutoring Systems. pp. 52–59. Springer International Publishing. Cham. bibtex

@InProceedings{10.1007/978-3-030-80421-3_6,
author="Sychev, Oleg
and Anikin, Anton
and Penskoy, Nikita
and Denisov, Mikhail
and Prokudin, Artem",
editor="Cristea, Alexandra I.
and Troussas, Christos",
title="CompPrehension - Model-Based Intelligent Tutoring System on Comprehension Level",
booktitle="Intelligent Tutoring Systems",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="52--59",
abstract="Intelligent tutoring systems become increasingly common in assisting human learners, but they are often aimed at isolated domain tasks without creating a scaffolding system from lower- to higher-level cognitive skills. We designed and implemented an intelligent tutoring system CompPrehension aimed at the comprehension level of Bloom's taxonomy that often gets neglected in favour of the higher levels. The system features plugin-based architecture, easing adding new domains and learning strategies; using formal models and software reasoners to solve the problems and judge the answers; and generating explanatory feedback and follow-up questions to stimulate the learners' thinking. The architecture and workflow are shown. We demonstrate the process of interacting with the system in the Control Flow Statements domain. The advantages and limits of the developed system are discussed.",
isbn="978-3-030-80421-3",
thanks = {rfbr-20-07-00764}
}

Abstract Intelligent tutoring systems become increasingly common in assisting human learners, but they are often aimed at isolated domain tasks without creating a scaffolding system from lower- to higher-level cognitive skills. We designed and implemented an intelligent tutoring system CompPrehension aimed at the comprehension level of Bloom's taxonomy that often gets neglected in favour of the higher levels. The system features plugin-based architecture, easing adding new domains and learning strategies; using formal models and software reasoners to solve the problems and judge the answers; and generating explanatory feedback and follow-up questions to stimulate the learners' thinking. The architecture and workflow are shown. We demonstrate the process of interacting with the system in the Control Flow Statements domain. The advantages and limits of the developed system are discussed.

Oleg Sychev, Dmitrii Sasov, Pavel Chechetkin (2021) Developing An Understanding Of Variables And Expressions In Introductory Programming Courses. In EpSBS - Volume 102 - NININS 2020. pp. 1019-1028. European Publisher. doi web bibtex

@inproceedings{13163,
    author       = {Oleg Sychev and Dmitrii Sasov and Pavel Chechetkin},
    title        = {Developing An Understanding Of Variables And Expressions In Introductory Programming Courses},
    booktitle    = {EpSBS - Volume 102 - NININS 2020},
    year         = {2021},
    pages        = {1019-1028},
    publisher    = {European Publisher},
    doi          = {10.15405/epsbs.2021.02.02.126},
    url          = {https://doi.org/10.15405/epsbs.2021.02.02.126},
    thanks = {rfbr-20-07-00764}
}

Oleg Sychev, Anton Anikin, Mikhail Denisov (2021) Inference Engines Performance in Reasoning Tasks for Intelligent Tutoring Systems. In Computational Science and Its Applications textendash ICCSA 2021. pp. 471–482. Springer International Publishing. doi web bibtex

@incollection{Sychev2021,
  doi = {10.1007/978-3-030-86960-1_33},
  url = {https://doi.org/10.1007/978-3-030-86960-1_33},
  year = {2021},
  publisher = {Springer International Publishing},
  pages = {471--482},
  author = {Oleg Sychev and Anton Anikin and Mikhail Denisov},
  title = {Inference Engines Performance in Reasoning Tasks for Intelligent Tutoring Systems},
  booktitle = {Computational Science and Its Applications {\textendash} {ICCSA} 2021},
  thanks = {rfbr-20-07-00764}
}

Oleg Sychev, Nikita Penskoy, Anton Anikin, Mikhail Denisov, Artem Prokudin (2021) Improving comprehension: Intelligent tutoring system explaining the domain rules when students break them. Education Sciences 11 (11) MDPI. doi web bibtex

@ARTICLE{Sychev2021mdpi,
author={Oleg Sychev and Nikita Penskoy and Anton Anikin and Mikhail Denisov and Artem Prokudin},
title={Improving comprehension: Intelligent tutoring system explaining the domain rules when students break them},
journal={Education Sciences},
year={2021},
volume={11},
number={11},
doi={10.3390/educsci11110719},
art_number={719},
url={https://www.mdpi.com/2227-7102/11/11/719},
affiliation={Software Engineering Department, Electronics and Computing Machinery Faculty, Volgograd State Technical University, Volgograd, 400005, Russian Federation},
abstract={Intelligent tutoring systems have become increasingly common in assisting students but are often aimed at isolated subject-domain tasks without creating a scaffolding system from lower-to higher-level cognitive skills, with low-level skills often neglected. We designed and developed an intelligent tutoring system, CompPrehension, which aims to improve the comprehension level of Bloom’s taxonomy. The system features plug-in-based architecture, easily adding new subject domains and learning strategies. It uses formal models and software reasoners to solve the problems and judge the answers, and generates explanatory feedback about the broken domain rules and follow-up questions to stimulate the students’ thinking. We developed two subject domain models: an Expressions domain for teaching the expression order of evaluation, and a Control Flow Statements domain for code-tracing tasks. The chief novelty of our research is that the developed models are capable of automatic problem classification, determining the knowledge required to solve them and so the pedagogical conditions to use the problem without human participation. More than 100 undergraduate first-year Computer Science students took part in evaluating the system. The results in both subject domains show medium but statistically significant learning gains after using the system for a few days; students with worse previous knowledge gained more. In the Control Flow Statements domain, the number of completed questions correlates positively with the post-test grades and learning gains. The students’ survey showed a slightly positive perception of the system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.},
correspondence_address1={Sychev, O.; Software Engineering Department, Russian Federation; эл. почта: o_sychev@vstu.ru; Anikin, A.; Software Engineering Department, Russian Federation; эл. почта: anton.anikin@vstu.ru},
publisher={MDPI},
issn={22277102},
language={English},
abbrev_source_title={Educ. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract Intelligent tutoring systems have become increasingly common in assisting students but are often aimed at isolated subject-domain tasks without creating a scaffolding system from lower-to higher-level cognitive skills, with low-level skills often neglected. We designed and developed an intelligent tutoring system, CompPrehension, which aims to improve the comprehension level of Bloom’s taxonomy. The system features plug-in-based architecture, easily adding new subject domains and learning strategies. It uses formal models and software reasoners to solve the problems and judge the answers, and generates explanatory feedback about the broken domain rules and follow-up questions to stimulate the students’ thinking. We developed two subject domain models: an Expressions domain for teaching the expression order of evaluation, and a Control Flow Statements domain for code-tracing tasks. The chief novelty of our research is that the developed models are capable of automatic problem classification, determining the knowledge required to solve them and so the pedagogical conditions to use the problem without human participation. More than 100 undergraduate first-year Computer Science students took part in evaluating the system. The results in both subject domains show medium but statistically significant learning gains after using the system for a few days; students with worse previous knowledge gained more. In the Control Flow Statements domain, the number of completed questions correlates positively with the post-test grades and learning gains. The students’ survey showed a slightly positive perception of the system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

O. Sychev, A. Anikin, G. Terekhov (2021) Demonstrating Concepts through Visual Simulators: Two Cases in the Programming Domain. Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2010-October IEEE Computer Society. doi web bibtex

@CONFERENCE{Sychev2021_2,
author={Sychev, O. and Anikin, A. and Terekhov, G.},
title={Demonstrating Concepts through Visual Simulators: Two Cases in the Programming Domain},
journal={Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC},
year={2021},
volume={2010-October},
doi={10.1109/VL/HCC51201.2021.9576398},
url={https://ieeexplore.ieee.org/document/9576398},
affiliation={Volgograd State Technical University, Software Engineering Department, Volgograd, Russian Federation},
abstract={One of the ways to demonstrate subject-domain concepts is to let the learner play in the domain-related sandbox, while receiving the explanations of the domain laws that were broken when the user makes a wrong move. This can help the learners who understand definitions of the concepts poorly. We present two visual simulators for demonstrating concept properties and domain laws, implemented as web applications. They can be used to study programming, enabling trial-and-error learning, supported by the error messages, explaining why the user's action was wrong. © 2021 IEEE.},
editor={Harms K., Cunha J., Oney S., Kelleher C.},
publisher={IEEE Computer Society},
issn={19436092},
isbn={9781665445924},
language={English},
abbrev_source_title={Proc. of IEEE Symp. Vis. Lang. Hum.-Cent. Comput., VL/HCC},
thanks = {rfbr-20-07-00764}
}

Abstract One of the ways to demonstrate subject-domain concepts is to let the learner play in the domain-related sandbox, while receiving the explanations of the domain laws that were broken when the user makes a wrong move. This can help the learners who understand definitions of the concepts poorly. We present two visual simulators for demonstrating concept properties and domain laws, implemented as web applications. They can be used to study programming, enabling trial-and-error learning, supported by the error messages, explaining why the user's action was wrong. © 2021 IEEE.

A. Anikin, O. Sychev, M. Denisov (2021) Ontology reasoning for explanatory feedback generation to teach how algorithms work. Frontiers in Artificial Intelligence and Applications 338 pp. V-VI. IOS Press BV. doi web bibtex

@ARTICLE{Anikin2021_3,
author={Anikin, A. and Sychev, O. and Denisov, M.},
title={Ontology reasoning for explanatory feedback generation to teach how algorithms work},
journal={Frontiers in Artificial Intelligence and Applications},
year={2021},
volume={338},
pages={V-VI},
doi={10.3233/FAIA210100},
art_number={239-244},
url={https://ebooks.iospress.nl/doi/10.3233/FAIA210100},
affiliation={Volgograd State Technical University, Russian Federation; Software Engineering School, Volgograd, Russian Federation},
abstract={Developing algorithms using control structures and understanding their building blocks are essential skills in mastering programming. Ontologies and software reasoning is a promising method for developing intelligent tutoring systems in well-defined domains (like programming languages and algorithms); it can be used for many kinds of teaching tasks. In this work, we used a formal model consisting of production rules for Apache Jena reasoner as a basis for developing a constraint-based tutor for introductory programming domain. The tutor can determine fault reasons for any incorrect answer that a student can enter. The problem the student should solve is building an execution trace for the given algorithm. The problem is a closed-ended question that requires arranging given actions in the (unique) correct order; some actions can be used several times, while others can be omitted. Using formal reasoning to check domain constraints allowed us to provide explanatory feedback for all kinds of errors students can make. © 2021 The authors and IOS Press.},
editor={Frasson C., Kabassi K., Voulodimos A.},
publisher={IOS Press BV},
issn={09226389},
isbn={9781643682044},
language={English},
abbrev_source_title={Front. Artif. Intell. Appl.},
thanks = {rfbr-20-07-00764}
}

Abstract Developing algorithms using control structures and understanding their building blocks are essential skills in mastering programming. Ontologies and software reasoning is a promising method for developing intelligent tutoring systems in well-defined domains (like programming languages and algorithms); it can be used for many kinds of teaching tasks. In this work, we used a formal model consisting of production rules for Apache Jena reasoner as a basis for developing a constraint-based tutor for introductory programming domain. The tutor can determine fault reasons for any incorrect answer that a student can enter. The problem the student should solve is building an execution trace for the given algorithm. The problem is a closed-ended question that requires arranging given actions in the (unique) correct order; some actions can be used several times, while others can be omitted. Using formal reasoning to check domain constraints allowed us to provide explanatory feedback for all kinds of errors students can make. © 2021 The authors and IOS Press.

M. Denisov, A. Anikin, O. Sychev, A. Katyshev (2021) Program execution comprehension modelling for algorithmic languages learning using ontology-based techniques. Advances in Intelligent Systems and Computing 1184 pp. 256-269. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Denisov2021256,
author={Denisov, M. and Anikin, A. and Sychev, O. and Katyshev, A.},
title={Program execution comprehension modelling for algorithmic languages learning using ontology-based techniques},
journal={Advances in Intelligent Systems and Computing},
year={2021},
volume={1184},
pages={256-269},
doi={10.1007/978-981-15-5859-7_25},
url={https://link.springer.com/chapter/10.1007%2F978-981-15-5859-7_25},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation; Software Engineering School, Volgograd, Russian Federation},
abstract={In this paper, we propose an ontology-based approach to model a program execution comprehension so to be able to explain to the novice programmer the essence of his/her error. We have studied the algorithmic languages model operating with actions and basic control structures (“sequence,” “branching,” and “looping”) and designed the rules to capture any deviation from the permissible. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.},
correspondence_address1={Anikin, A.; Software Engineering SchoolRussian Federation; эл. почта: Anton@Anikin.name},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={21945357},
language={English},
abbrev_source_title={Adv. Intell. Sys. Comput.},
thanks = {rfbr-18-07-00032}
}

Abstract In this paper, we propose an ontology-based approach to model a program execution comprehension so to be able to explain to the novice programmer the essence of his/her error. We have studied the algorithmic languages model operating with actions and basic control structures (“sequence,” “branching,” and “looping”) and designed the rules to capture any deviation from the permissible. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

O. Sychev, Y. Kamennov (2021) Eligibility of English Hypernymy Resources for Extracting Knowledge from Natural-Language Texts. Advances in Intelligent Systems and Computing 1310 pp. 501-507. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Sychev2021501,
author={Sychev, O. and Kamennov, Y.},
title={Eligibility of English Hypernymy Resources for Extracting Knowledge from Natural-Language Texts},
journal={Advances in Intelligent Systems and Computing},
year={2021},
volume={1310},
pages={501-507},
doi={10.1007/978-3-030-65596-9_61},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-65596-9_61},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={A common subtask of knowledge acquisition from natural-language texts is classifying words and recognizing entities and actions in the text. It is used in the analysis of both scientific and narrative texts. Thesauri and lexical databases containing hypernymy relationship between synsets may be a useful resource for entity and action recognition. In this study, we compared the performance of three major English thesauri containing hypernymy relationship in different forms - WordNet, Roget’s Thesaurus, and FrameNet - on 6 word-meaning categories that are used for the analysis of narrative and scientific natural-language texts. The results show that WordNet contains more words than FrameNet, and is more suitable for scientific texts, but FrameNet contains better-defined hypernyms and shows better precision for many narrative natural-language tasks, especially for verbs. Roget’s Thesaurus performance is average between WordNet and FrameNet in most word-meaning categories Enhancing FrameNet by adding more lexical units to existing frames would allow creating a powerful resource for entity and action recognition in text analysis. Fixing WordNet problems require revising its system of hypernyms. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
correspondence_address1={Sychev, O.; Volgograd State Technical UniversityRussian Federation; эл. почта: oasychev@gmail.com},
editor={Samsonovich A.V., Gudwin R.R., Simoes A.d.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={21945357},
isbn={9783030655952},
language={English},
abbrev_source_title={Adv. Intell. Sys. Comput.},
thanks = {rfbr-20-07-00764}
}

Abstract A common subtask of knowledge acquisition from natural-language texts is classifying words and recognizing entities and actions in the text. It is used in the analysis of both scientific and narrative texts. Thesauri and lexical databases containing hypernymy relationship between synsets may be a useful resource for entity and action recognition. In this study, we compared the performance of three major English thesauri containing hypernymy relationship in different forms - WordNet, Roget’s Thesaurus, and FrameNet - on 6 word-meaning categories that are used for the analysis of narrative and scientific natural-language texts. The results show that WordNet contains more words than FrameNet, and is more suitable for scientific texts, but FrameNet contains better-defined hypernyms and shows better precision for many narrative natural-language tasks, especially for verbs. Roget’s Thesaurus performance is average between WordNet and FrameNet in most word-meaning categories Enhancing FrameNet by adding more lexical units to existing frames would allow creating a powerful resource for entity and action recognition in text analysis. Fixing WordNet problems require revising its system of hypernyms. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

O. Sychev (2021) CorrectWriting: Open-Ended Question with Hints for Teaching Programming-Language Syntax. Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE pp. 623-624. Association for Computing Machinery. doi web bibtex

@CONFERENCE{Sychev2021623,
author={Sychev, O.},
title={CorrectWriting: Open-Ended Question with Hints for Teaching Programming-Language Syntax},
journal={Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE},
year={2021},
pages={623-624},
doi={10.1145/3456565.3460030},
url={https://dl.acm.org/doi/10.1145/3456565.3460030},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={Teaching students to construct correct statements in programming languages is an important part of introductory programming courses. While modern development environments highlight syntax errors, they do not stimulate thinking in grammatical terms to help the student understand and memorize syntax rules. To facilitate learning syntax, we developed CorrectWriting, a question-type plug-in for the popular LMS Moodle. It finds mistakes in token order and composition and detects typos, including missing and extraneous separators. Mistake messages use teacher-supplied token descriptions to show the grammatical role of each wrong token. Hints are provided about students' mistakes. CorrectWriting questions are actively used by the students of Volgograd State Technical University to prepare for classwork. © 2021 Owner/Author.},
correspondence_address1={Sychev, O.; Volgograd State Technical UniversityRussian Federation; эл. почта: oasychev@gmail.com},
publisher={Association for Computing Machinery},
issn={1942647X},
isbn={9781450383974},
language={English},
abbrev_source_title={Annu. Conf. Innov. Technol. Comput. Sci. Educ. ITiCSE},
thanks = {rfbr-20-07-00764}
}

Abstract Teaching students to construct correct statements in programming languages is an important part of introductory programming courses. While modern development environments highlight syntax errors, they do not stimulate thinking in grammatical terms to help the student understand and memorize syntax rules. To facilitate learning syntax, we developed CorrectWriting, a question-type plug-in for the popular LMS Moodle. It finds mistakes in token order and composition and detects typos, including missing and extraneous separators. Mistake messages use teacher-supplied token descriptions to show the grammatical role of each wrong token. Hints are provided about students' mistakes. CorrectWriting questions are actively used by the students of Volgograd State Technical University to prepare for classwork. © 2021 Owner/Author.

O.A. Sychev, A.A. Prokudin, O.E. Evtushenko, O.V. Toporkova (2021) The impact of formative quizzes using CorrectWriting question type on learning word order in an ESL course. Journal of Physics: Conference Series 1801 (1) IOP Publishing Ltd. doi web bibtex

@CONFERENCE{Sychev2021_6,
author={Sychev, O.A. and Prokudin, A.A. and Evtushenko, O.E. and Toporkova, O.V.},
title={The impact of formative quizzes using CorrectWriting question type on learning word order in an ESL course},
journal={Journal of Physics: Conference Series},
year={2021},
volume={1801},
number={1},
doi={10.1088/1742-6596/1801/1/012011},
art_number={012011},
url={https://iopscience.iop.org/article/10.1088/1742-6596/1801/1/012011},
affiliation={Volgograd State Technical University, Lenina Avenue 28, Volgograd, 400005, Russian Federation},
abstract={Studying word order in English sentences is a problem for ESL students whose native languages allow flexible word orders. Developing skills in formulating English sentences often requires trial-and-error process that takes time and requires supervision. Quiz software that is able to analyse students' answers, and give meaningful feedback on mistakes in word order and hints on fixing them allows training without teacher's supervision that greatly enhances the amount of attempts a student can do. In this study, we used CorrectWriting question type for Moodle LMS to create formative and summative quizzes for Russian students learning English as a second language. The experiments show that the students who made more than one attempt of formative quizzes had significantly better learning gains than the students who didn't use formative quizzes or attempted them only once. It also showed vulnerabilities in question design that need to be fixed to utilise software features better in learning process. © Published under licence by IOP Publishing Ltd.},
correspondence_address1={Sychev, O.A.; Volgograd State Technical University, Lenina Avenue 28, Russian Federation; эл. почта: oasychev@gmail.com},
publisher={IOP Publishing Ltd},
issn={17426588},
language={English},
abbrev_source_title={J. Phys. Conf. Ser.},
thanks = {rfbr-20-07-00764}
}

Abstract Studying word order in English sentences is a problem for ESL students whose native languages allow flexible word orders. Developing skills in formulating English sentences often requires trial-and-error process that takes time and requires supervision. Quiz software that is able to analyse students' answers, and give meaningful feedback on mistakes in word order and hints on fixing them allows training without teacher's supervision that greatly enhances the amount of attempts a student can do. In this study, we used CorrectWriting question type for Moodle LMS to create formative and summative quizzes for Russian students learning English as a second language. The experiments show that the students who made more than one attempt of formative quizzes had significantly better learning gains than the students who didn't use formative quizzes or attempted them only once. It also showed vulnerabilities in question design that need to be fixed to utilise software features better in learning process. © Published under licence by IOP Publishing Ltd.

O. Sychev (2021) Visualizing Program State as a Clustered Graph for Learning Programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12909 LNAI pp. 404-407. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Sychev2021404,
author={Sychev, O.},
title={Visualizing Program State as a Clustered Graph for Learning Programming},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year={2021},
volume={12909 LNAI},
pages={404-407},
doi={10.1007/978-3-030-86062-2_41},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-86062-2_41},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The poster presents a method of visualizing the program state as a diagram of data elements that can both include nested elements and reference other elements. It differs from the known methods because it allows nested objects and arrays; the method also acknowledges high-level data structures like containers and iterators. Layout methods for graphs of this complexity are discussed, and examples of the resulting graphs are provided. The approach was used in computer science courses; the survey showed that it was popular among middle- and low-performing students while high-performing students preferred a professional tool, giving more compact images. Educational uses of the generated diagrams are discussed. © 2021, Springer Nature Switzerland AG.},
correspondence_address1={Sychev, O.; Volgograd State Technical UniversityRussian Federation; эл. почта: o_sychev@vstu.ru},
editor={Basu A., Stapleton G., Linker S., Legg C., Manalo E., Viana P.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={03029743},
isbn={9783030860615},
language={English},
abbrev_source_title={Lect. Notes Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract The poster presents a method of visualizing the program state as a diagram of data elements that can both include nested elements and reference other elements. It differs from the known methods because it allows nested objects and arrays; the method also acknowledges high-level data structures like containers and iterators. Layout methods for graphs of this complexity are discussed, and examples of the resulting graphs are provided. The approach was used in computer science courses; the survey showed that it was popular among middle- and low-performing students while high-performing students preferred a professional tool, giving more compact images. Educational uses of the generated diagrams are discussed. © 2021, Springer Nature Switzerland AG.

M. Denisov, A. Anikin, O. Sychev (2021) Dynamic Flowcharts for Enhancing Learners’ Understanding of the Control Flow During Programming Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12909 LNAI pp. 408-411. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Denisov2021408,
author={Denisov, M. and Anikin, A. and Sychev, O.},
title={Dynamic Flowcharts for Enhancing Learners’ Understanding of the Control Flow During Programming Learning},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year={2021},
volume={12909 LNAI},
pages={408-411},
doi={10.1007/978-3-030-86062-2_42},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-86062-2_42},
affiliation={Volgograd State Technical University, Lenin Ave, 28, Volgograd, 400005, Russian Federation},
abstract={In introductory programming learning, flowcharts are often used to help students comprehend patterns of behavior of control flow statements like alternatives, loops, and switches. The use of flowcharts in assignments along with lectures can increase their learning effect. In some areas, the potential of flowcharts remains largely underestimated. Flowcharts are rare in intelligent learning systems for learning programming, although class, object, and sequence diagrams are quite popular. This poster describes the implementation of a non-editable flowchart widget in our intelligent programming tutor on control flow structures (hereinafter referred to as the exerciser). In normal use, the student chooses the next correct action in the program text (algorithm), i.e., makes one transition through the flowchart. Our exerciser allows making a wrong choice and gives a text hint explaining the reason for incorrectness. The wrong or inexistent transition is also displayed on the flowchart to help localize the error. © 2021, Springer Nature Switzerland AG.},
correspondence_address1={Anikin, A.; Volgograd State Technical University, Lenin Ave, 28, Russian Federation; эл. почта: anton.anikin@vstu.ru},
editor={Basu A., Stapleton G., Linker S., Legg C., Manalo E., Viana P.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={03029743},
isbn={9783030860615},
language={English},
abbrev_source_title={Lect. Notes Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract In introductory programming learning, flowcharts are often used to help students comprehend patterns of behavior of control flow statements like alternatives, loops, and switches. The use of flowcharts in assignments along with lectures can increase their learning effect. In some areas, the potential of flowcharts remains largely underestimated. Flowcharts are rare in intelligent learning systems for learning programming, although class, object, and sequence diagrams are quite popular. This poster describes the implementation of a non-editable flowchart widget in our intelligent programming tutor on control flow structures (hereinafter referred to as the exerciser). In normal use, the student chooses the next correct action in the program text (algorithm), i.e., makes one transition through the flowchart. Our exerciser allows making a wrong choice and gives a text hint explaining the reason for incorrectness. The wrong or inexistent transition is also displayed on the flowchart to help localize the error. © 2021, Springer Nature Switzerland AG.

V. Uglev, O. Sychev (2021) Concentrating Competency Profile Data into Cognitive Map of Knowledge Diagnosis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12909 LNAI pp. 443-446. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Uglev2021443,
author={Uglev, V. and Sychev, O.},
title={Concentrating Competency Profile Data into Cognitive Map of Knowledge Diagnosis},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year={2021},
volume={12909 LNAI},
pages={443-446},
doi={10.1007/978-3-030-86062-2_46},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-86062-2_46},
affiliation={Siberian Federal University, Zheleznogorsk, Russian Federation; Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The paper describes the process of aggregating primary learning data in the form of learning digital footprints for managing educational process using cognitive visualization techniques. The over-arching process of transition from the learning data to competency diagrams and concentrate them into Cognitive Maps of Cnowledge Diagnosis that. The competency profile, represented as a radar-chart diagram, is compressed into a cognitive map, allowing interpreting this information during decision making by faculty and administrative staff. This allows generalizing results for groups of students. The results of using competency profiles and respective cognitive maps to analyze the results of summative assessments, final, and cross-curricular exams are provided as an illustration of the proposed approach. © 2021, Springer Nature Switzerland AG.},
correspondence_address1={Uglev, V.; Siberian Federal UniversityRussian Federation; эл. почта: vauglev@sfu-kras.ru},
editor={Basu A., Stapleton G., Linker S., Legg C., Manalo E., Viana P.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={03029743},
isbn={9783030860615},
language={English},
abbrev_source_title={Lect. Notes Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract The paper describes the process of aggregating primary learning data in the form of learning digital footprints for managing educational process using cognitive visualization techniques. The over-arching process of transition from the learning data to competency diagrams and concentrate them into Cognitive Maps of Cnowledge Diagnosis that. The competency profile, represented as a radar-chart diagram, is compressed into a cognitive map, allowing interpreting this information during decision making by faculty and administrative staff. This allows generalizing results for groups of students. The results of using competency profiles and respective cognitive maps to analyze the results of summative assessments, final, and cross-curricular exams are provided as an illustration of the proposed approach. © 2021, Springer Nature Switzerland AG.

E. Novozhenina, O. Sychev, O. Toporkova, O. Evtushenko (2021) Teaching English Word Order with CorrectWriting Software. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12951 LNCS pp. 681-692. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Novozhenina2021681,
author={Novozhenina, E. and Sychev, O. and Toporkova, O. and Evtushenko, O.},
title={Teaching English Word Order with CorrectWriting Software},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year={2021},
volume={12951 LNCS},
pages={681-692},
doi={10.1007/978-3-030-86970-0_47},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-86970-0_47},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The article looks into the problem of using interactive computer technologies in technology-enhanced teaching English at a technical university. An electronic course “English Word Order” using CorrectWriting software for Moodle LMS was developed and used to teach students of various levels of education. The system of formative and summative assessments regarding the word order of English sentences was studied. The students’ responses to CorrectWriting questions were analyzed using the Longest Common Subsequence algorithm, allowing determining misplaced, missing and extraneous words. During formative assessments, the students were offered automatic hints on how to fix their mistakes without having to wait for feedback from the teacher. The learning gains and the student survey prove the efficiency of the developed online course which helps to improve students’ grammar skills during the classes and unsupervised work. The study also notes a positive role of electronic teaching materials in optimizing the technological and organizational support of the educational process. Further work on enhancing the developed course and software is outlined. © 2021, Springer Nature Switzerland AG.},
correspondence_address1={Sychev, O.; Volgograd State Technical UniversityRussian Federation; эл. почта: o_sychev@vstu.ru},
editor={Gervasi O., Murgante B., Misra S., Garau C., Blecic I., Taniar D., Apduhan B.O., Rocha A.M., Tarantino E., Torre C.M.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={03029743},
isbn={9783030869694},
language={English},
abbrev_source_title={Lect. Notes Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract The article looks into the problem of using interactive computer technologies in technology-enhanced teaching English at a technical university. An electronic course “English Word Order” using CorrectWriting software for Moodle LMS was developed and used to teach students of various levels of education. The system of formative and summative assessments regarding the word order of English sentences was studied. The students’ responses to CorrectWriting questions were analyzed using the Longest Common Subsequence algorithm, allowing determining misplaced, missing and extraneous words. During formative assessments, the students were offered automatic hints on how to fix their mistakes without having to wait for feedback from the teacher. The learning gains and the student survey prove the efficiency of the developed online course which helps to improve students’ grammar skills during the classes and unsupervised work. The study also notes a positive role of electronic teaching materials in optimizing the technological and organizational support of the educational process. Further work on enhancing the developed course and software is outlined. © 2021, Springer Nature Switzerland AG.

V. Uglev, O. Sychev (2021) Creating and Visualising Cognitive Maps of Knowledge Diagnosis During the Processing of Learning Digital Footprint. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12677 LNCS pp. 93-98. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Uglev202193,
author={Uglev, V. and Sychev, O.},
title={Creating and Visualising Cognitive Maps of Knowledge Diagnosis During the Processing of Learning Digital Footprint},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year={2021},
volume={12677 LNCS},
pages={93-98},
doi={10.1007/978-3-030-80421-3_11},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-86970-0_47},
affiliation={Siberian Federal University, Zheleznogorsk, Russian Federation; Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The paper describes the problem of creating a single mapping of the learning situation during the processing of digital footprint and decision making in intelligent tutoring systems. We propose creating a Cognitive Map of Knowledge Diagnosis as a way of summarising data in the digital footprint. The elements of this cognitive map and the details of their visualisation are described. The results of the use of cognitive maps are demonstrated on the example of personalising the content of an online learning course and providing detailed feedback. © 2021, Springer Nature Switzerland AG.},
correspondence_address1={Uglev, V.; Siberian Federal UniversityRussian Federation; эл. почта: uglev-v@yandex.ru},
editor={Cristea A.I., Troussas C.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={03029743},
isbn={9783030804206},
language={English},
abbrev_source_title={Lect. Notes Comput. Sci.},
thanks = {rfbr-20-07-00764}
}

Abstract The paper describes the problem of creating a single mapping of the learning situation during the processing of digital footprint and decision making in intelligent tutoring systems. We propose creating a Cognitive Map of Knowledge Diagnosis as a way of summarising data in the digital footprint. The elements of this cognitive map and the details of their visualisation are described. The results of the use of cognitive maps are demonstrated on the example of personalising the content of an online learning course and providing detailed feedback. © 2021, Springer Nature Switzerland AG.

D. Litovkin, D. Dontsov, A. Anikin, O. Sychev (2021) Suitability of Object-Role Modeling Diagrams as an Intermediate Model for Ontology Engineering: Testing the Rules for Mapping. Advances in Intelligent Systems and Computing 1310 pp. 188-194. Springer Science and Business Media Deutschland GmbH. doi web bibtex

@ARTICLE{Litovkin2021188,
author={Litovkin, D. and Dontsov, D. and Anikin, A. and Sychev, O.},
title={Suitability of Object-Role Modeling Diagrams as an Intermediate Model for Ontology Engineering: Testing the Rules for Mapping},
journal={Advances in Intelligent Systems and Computing},
year={2021},
volume={1310},
pages={188-194},
doi={10.1007/978-3-030-65596-9_24},
url={https://link.springer.com/chapter/10.1007%2F978-3-030-65596-9_24},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={Creating and understanding ontologies using OWL2 language is a hard, time-consuming task for both domain experts and consumers of knowledge (for example, teachers and students). Using Object-Role Modeling diagrams as an intermediate model facilitates this process. To achieve this, the method of mapping ORM2 diagrams to OWL2 ontologies and vice versa is necessary. Such methods were proposed in different works, but their suitability and possible errors are in doubt. In this paper, we propose a method of evaluating how well existing rules of mapping follow ORM semantics. Several ontologies were created using mapping rules and tested. During testing, a significant difference between ORM2 and OWL2 basic properties and assumptions were discovered. This difference require updating the mapping rules. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
correspondence_address1={Anikin, A.; Volgograd State Technical UniversityRussian Federation; эл. почта: anton@anikin.name},
editor={Samsonovich A.V., Gudwin R.R., Simoes A.d.},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={21945357},
isbn={9783030655952},
language={English},
abbrev_source_title={Adv. Intell. Sys. Comput.},
thanks = {rfbr-20-07-00764}
}

Abstract Creating and understanding ontologies using OWL2 language is a hard, time-consuming task for both domain experts and consumers of knowledge (for example, teachers and students). Using Object-Role Modeling diagrams as an intermediate model facilitates this process. To achieve this, the method of mapping ORM2 diagrams to OWL2 ontologies and vice versa is necessary. Such methods were proposed in different works, but their suitability and possible errors are in doubt. In this paper, we propose a method of evaluating how well existing rules of mapping follow ORM semantics. Several ontologies were created using mapping rules and tested. During testing, a significant difference between ORM2 and OWL2 basic properties and assumptions were discovered. This difference require updating the mapping rules. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

O. Sychev, M. Denisov, G. Terekhov (2021) How it Works: Algorithms-A Tool for Developing an Understanding of Control Structures. Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE pp. 621-622. Association for Computing Machinery. doi web bibtex

@CONFERENCE{Sychev2021621,
author={Sychev, O. and Denisov, M. and Terekhov, G.},
title={How it Works: Algorithms-A Tool for Developing an Understanding of Control Structures},
journal={Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE},
year={2021},
pages={621-622},
doi={10.1145/3456565.3460032},
url={https://dl.acm.org/doi/10.1145/3456565.3460032},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={Developing an understanding of control structures is one of the important tasks in introductory programming courses. To facilitate active learning with immediate feedback, we developed a constraint-based tutor, "How it Works: Algorithms,"that asks students to build an execution trace of the given algorithm and provides explanatory feedback about the mistakes the student made. The reasons for the student's faults are determined by an inference engine, using a set of rules describing the subject domain. Teachers can create exercises using a simple visual block-based interface and sending them to students as permanent links. © 2021 Owner/Author.},
publisher={Association for Computing Machinery},
issn={1942647X},
isbn={9781450383974},
language={English},
abbrev_source_title={Annu. Conf. Innov. Technol. Comput. Sci. Educ. ITiCSE},
thanks = {rfbr-20-07-00764}
}

Abstract Developing an understanding of control structures is one of the important tasks in introductory programming courses. To facilitate active learning with immediate feedback, we developed a constraint-based tutor, “How it Works: Algorithms,”that asks students to build an execution trace of the given algorithm and provides explanatory feedback about the mistakes the student made. The reasons for the student's faults are determined by an inference engine, using a set of rules describing the subject domain. Teachers can create exercises using a simple visual block-based interface and sending them to students as permanent links. © 2021 Owner/Author.

2020 (2)

Oleg Sychev, Anton Anikin, Artem Prokudin (2020) Automatic grading and hinting in open-ended text questions. Cognitive Systems Research 59 pp. 264 - 272. doi web bibtex

@article{SYCHEV2020,
title = "Automatic grading and hinting in open-ended text questions",
journal = "Cognitive Systems Research",
volume = "59",
pages = "264 - 272",
year = "2020",
issn = "1389-0417",
doi = "https://doi.org/10.1016/j.cogsys.2019.09.025",
url = "http://www.sciencedirect.com/science/article/pii/S1389041719304978",
author = "Oleg Sychev and Anton Anikin and Artem Prokudin",
thanks = {rfbr-18-07-00032}
}

Dmitry Litovkin, Anton Anikin, Marina Kultsova (2020) Interactive Visualization of Ontology-Based Conceptual Domain Models in Learning and Scientific Research. In Fourth International Congress on Information and Communication Technology. pp. 365–374. Springer Singapore. Singapore. doi bibtex

@InProceedings{10.1007/978-981-15-0637-6_31,
doi="10.1007/978-981-15-0637-6_31",
author="Litovkin, Dmitry
and Anikin, Anton
and Kultsova, Marina",
editor="Yang, Xin-She
and Sherratt, Simon
and Dey, Nilanjan
and Joshi, Amit",
title="Interactive Visualization of Ontology-Based Conceptual Domain Models in Learning and Scientific Research",
booktitle="Fourth International Congress on Information and Communication Technology",
year="2020",
publisher="Springer Singapore",
address="Singapore",
pages="365--374",
abstract="The paper presents an approach to knowledge transferring and sharing on the base of the semantic link network (SLN) representing expert knowledge in the explicit form. To provide an efficient SLN understanding, it is represented with a geometric graph which can be interactively visualized using a combination of the appropriate visualization methods. The coupling of these methods allows getting a different level of details of the SLN visualization in accordance with the user needs. The proposed approach is planned being implemented in the knowledge management system for learning and scientific research.",
isbn="978-981-15-0637-6",
thanks = {rfbr-18-07-00032, rfbr-18-47-340014}
}

Abstract The paper presents an approach to knowledge transferring and sharing on the base of the semantic link network (SLN) representing expert knowledge in the explicit form. To provide an efficient SLN understanding, it is represented with a geometric graph which can be interactively visualized using a combination of the appropriate visualization methods. The coupling of these methods allows getting a different level of details of the SLN visualization in accordance with the user needs. The proposed approach is planned being implemented in the knowledge management system for learning and scientific research.

2019 (7)

Anton Anikin, Oleg Sychev (jul 2019) Ontology-Based Modelling for Learning on Bloom's Taxonomy Comprehension Level. In Advances in Intelligent Systems and Computing. pp. 22–27. Springer International Publishing. doi web bibtex

@incollection{Anikin2019_2,
  doi = {10.1007/978-3-030-25719-4_4},
  url = {https://doi.org/10.1007/978-3-030-25719-4_4},
  year = {2019},
  month = jul,
  publisher = {Springer International Publishing},
  pages = {22--27},
  author = {Anton Anikin and Oleg Sychev},
  title = {Ontology-Based Modelling for Learning on Bloom's Taxonomy Comprehension Level},
  booktitle = {Advances in Intelligent Systems and Computing}
}

Oleg Sychev, Anton Anikin, Artem Prokudin (jul 2019) Methods of Determining Errors in Open-Ended Text Questions. In Advances in Intelligent Systems and Computing. pp. 521–526. Springer International Publishing. doi web bibtex

@incollection{Anikin2019_3,
  doi = {10.1007/978-3-030-25719-4_67},
  url = {https://doi.org/10.1007/978-3-030-25719-4_67},
  year = {2019},
  month = jul,
  publisher = {Springer International Publishing},
  pages = {521--526},
  author = {Oleg Sychev and Anton Anikin and Artem Prokudin},
  title = {Methods of Determining Errors in Open-Ended Text Questions},
  booktitle = {Advances in Intelligent Systems and Computing}
}

Anton Anikin, Dmitry Litovkin, Elena Sarkisova, Tatyana Petrova, Marina Kultsova (mar 2019) Ontology-based approach to decision-making support of conceptual domain models creating and using in learning and scientific research. IOP Conference Series: Materials Science and Engineering 483 pp. 012074. IOP Publishing. doi web bibtex

@article{Anikin_2019_1,
	doi = {10.1088/1757-899x/483/1/012074},
	url = {https://doi.org/10.1088%2F1757-899x%2F483%2F1%2F012074},
	year = 2019,
	month = {mar},
	publisher = {{IOP} Publishing},
	volume = {483},
	pages = {012074},
	author = {Anton Anikin and Dmitry Litovkin and Elena Sarkisova and Tatyana Petrova and Marina Kultsova},
	title = {Ontology-based approach to decision-making support of conceptual domain models creating and using in learning and scientific research},
	journal = {{IOP} Conference Series: Materials Science and Engineering},
	thanks = {rfbr-18-07-00032, rfbr-18-47-340014},
	abstract = {The paper presents an approach to knowledge management in learning and scientific research that allows increasing the availability of expert knowledge and reducing semantic noise during knowledge transfer. The availability of expert knowledge is ensured by transforming them from implicit into explicit form (in the form of Semantic Link Network). The reduction of semantic noise is achieved through the integration of knowledge in different forms and their personalization for different groups of knowledge recipients. In the paper, the tasks of decision-making support are formulated which should be performed by the knowledge management system on the base of the proposed approach.}
}

Abstract The paper presents an approach to knowledge management in learning and scientific research that allows increasing the availability of expert knowledge and reducing semantic noise during knowledge transfer. The availability of expert knowledge is ensured by transforming them from implicit into explicit form (in the form of Semantic Link Network). The reduction of semantic noise is achieved through the integration of knowledge in different forms and their personalization for different groups of knowledge recipients. In the paper, the tasks of decision-making support are formulated which should be performed by the knowledge management system on the base of the proposed approach.

A Anikin, A Katyshev, M Denisov, V Smirnov, D Litovkin (mar 2019) Using online update of distributional semantics models for decision-making support for concepts extraction in the domain ontology learning task. IOP Conference Series: Materials Science and Engineering 483 pp. 012073. IOP Publishing. doi web bibtex

@article{Anikin_2019_2,
	doi = {10.1088/1757-899x/483/1/012073},
	url = {https://doi.org/10.1088%2F1757-899x%2F483%2F1%2F012073},
	year = 2019,
	month = {mar},
	publisher = {{IOP} Publishing},
	volume = {483},
	pages = {012073},
	author = {A Anikin and A Katyshev and M Denisov and V Smirnov and D Litovkin},
	title = {Using online update of distributional semantics models for decision-making support for concepts extraction in the domain ontology learning task},
	journal = {{IOP} Conference Series: Materials Science and Engineering},
	thanks = {rfbr-18-07-00032},
	abstract = {Most of the information processed by computer systems is presented in the form of text corpuses. The number of such texts (as well as the corpus as a whole) only increases with time, and therefore the word processing tasks remain relevant to this day. Ontology allows to describe semantics using domain concepts and relations between them [1, 2]. In the ontology learning task, the ontology is dependent on quality of corpus which may not be readily available. There are different approaches to creating ontologies (including the use of different tools and frameworks). This paper discusses the use of word2vec (group of related models that are used to produce word embeddings) using online vocabulary update and extension of the original data corpus with additional training for the domain concepts extraction to automate the domain ontology creation.}
}

Abstract Most of the information processed by computer systems is presented in the form of text corpuses. The number of such texts (as well as the corpus as a whole) only increases with time, and therefore the word processing tasks remain relevant to this day. Ontology allows to describe semantics using domain concepts and relations between them [1, 2]. In the ontology learning task, the ontology is dependent on quality of corpus which may not be readily available. There are different approaches to creating ontologies (including the use of different tools and frameworks). This paper discusses the use of word2vec (group of related models that are used to produce word embeddings) using online vocabulary update and extension of the original data corpus with additional training for the domain concepts extraction to automate the domain ontology creation.

Marina Kultsova, Anastasiya Potseluico, Alexander Dvoryankin (2019) Ontology Based Personalization of Mobile Interfaces for People with Special Needs. In Creativity in Intelligent Technologies and Data Science. pp. 422–433. Springer International Publishing. Cham. doi bibtex

@InProceedings{10.1007/978-3-030-29750-3_33,
doi="10.1007/978-3-030-29750-3_33",
author="Kultsova, Marina
and Potseluico, Anastasiya
and Dvoryankin, Alexander",
editor="Kravets, Alla G.
and Groumpos, Peter P.
and Shcherbakov, Maxim
and Kultsova, Marina",
title="Ontology Based Personalization of Mobile Interfaces for People with Special Needs",
booktitle="Creativity in Intelligent Technologies and Data Science",
year="2019",
publisher="Springer International Publishing",
address="Cham",
pages="422--433",
abstract="The paper is devoted to a problem of interface personification for people with special needs on the base of information about their behavior during interaction with mobile applications. This work evolves our previous researches on the development of adaptive user interfaces. Much attention in this paper was given to the investigation of existing approaches to collecting and analyzing the information about user behavior and interaction context data as well as interface adaptation recommendations. The improved interface adaptation mechanism was developed and described based on the ontological representation of the interface patterns and knowledge about users and their interaction with a mobile application. The set of adaptation rules was developed and implemented in the ontology knowledge base. In the paper, we described the improved ontology model and some examples of ontological representation of interface patterns.",
isbn="978-3-030-29750-3",
thanks = {rfbr-18-07-00032}
}

Abstract The paper is devoted to a problem of interface personification for people with special needs on the base of information about their behavior during interaction with mobile applications. This work evolves our previous researches on the development of adaptive user interfaces. Much attention in this paper was given to the investigation of existing approaches to collecting and analyzing the information about user behavior and interaction context data as well as interface adaptation recommendations. The improved interface adaptation mechanism was developed and described based on the ontological representation of the interface patterns and knowledge about users and their interaction with a mobile application. The set of adaptation rules was developed and implemented in the ontology knowledge base. In the paper, we described the improved ontology model and some examples of ontological representation of interface patterns.

Dmitry Litovkin, Anton Anikin, Marina Kultsova (2019) Semantic Zooming Approach to Semantic Link Network Visualization. In Creativity in Intelligent Technologies and Data Science. pp. 81–95. Springer International Publishing. Cham. doi bibtex

@InProceedings{10.1007/978-3-030-29750-3_7,
doi="10.1007/978-3-030-29750-3_7",
author="Litovkin, Dmitry
and Anikin, Anton
and Kultsova, Marina",
editor="Kravets, Alla G.
and Groumpos, Peter P.
and Shcherbakov, Maxim
and Kultsova, Marina",
title="Semantic Zooming Approach to Semantic Link Network Visualization",
booktitle="Creativity in Intelligent Technologies and Data Science",
year="2019",
publisher="Springer International Publishing",
address="Cham",
pages="81--95",
abstract="In the paper, we described a semantic zooming approach to the visualization of special kind structures - semantic link networks (SLN), represented as a visual graph. The proposed approach allows decreasing semantic noise in SLN overview and navigation and also simplifies the process of understanding the domain studied with SLN by means of semantic zooming. We proposed priori importance levels of SLN items and semantic zooming scale to visualize the SLN with different details level. We designed an interactive SLN visualization process including the following SLN transformations: filtering SLN items, context collapse and expansion for SLN item, and changing the details in the visualized object representation in the geometric SLN graph. The transformation algorithms were developed, and also examples of SNL semantic zooming were described in details in the paper.",
isbn="978-3-030-29750-3",
thanks = {rfbr-18-07-00032, rfbr-18-47-340014}
}

Abstract In the paper, we described a semantic zooming approach to the visualization of special kind structures - semantic link networks (SLN), represented as a visual graph. The proposed approach allows decreasing semantic noise in SLN overview and navigation and also simplifies the process of understanding the domain studied with SLN by means of semantic zooming. We proposed priori importance levels of SLN items and semantic zooming scale to visualize the SLN with different details level. We designed an interactive SLN visualization process including the following SLN transformations: filtering SLN items, context collapse and expansion for SLN item, and changing the details in the visualized object representation in the geometric SLN graph. The transformation algorithms were developed, and also examples of SNL semantic zooming were described in details in the paper.

Anton Anikin, Oleg Sychev, Vladislav Gurtovoy (2019) Multi-level Modeling of Structural Elements of Natural Language Texts and Its Applications. In Biologically Inspired Cognitive Architectures 2018. pp. 1–8. Springer International Publishing. Cham. bibtex

@InProceedings{10.1007/978-3-319-99316-4_1,
author="Anikin, Anton
and Sychev, Oleg
and Gurtovoy, Vladislav",
editor="Samsonovich, Alexei V.",
title="Multi-level Modeling of Structural Elements of Natural Language Texts and Its Applications",
booktitle="Biologically Inspired Cognitive Architectures 2018",
year="2019",
publisher="Springer International Publishing",
address="Cham",
pages="1--8",
abstract="Methods of extracting knowledge in the analysis of large volumes of natural language texts are relevant for solving various problems in the field of analysis and generation of textual information, such as text analysis for extracting data, fact and semantics; presenting extracted information in a convenient for machine processing form (for example, ontology); classification and clustering texts, including thematic modeling; information retrieval (including thematic search, search based on the user model, ontology-based models, document sample based search); texts abstracting and annotating; developing of intelligent question-answering systems; generating texts of different types (fiction, marketing, weather forecasts etc.); as well as rewriting texts, preserving the meaning of the original text for presenting it to different target audiences. In order for such methods to work, it is necessary to construct and use models that adequately describe structural elements of the text on different levels (individual words, sentences, thematic text fragments), their characteristics and semantics, as well as relations between them, allowing to form higher-level structures. Such models should also take into account general characteristics of textual data: genre, purpose, target audience, scientific field and others. In this paper, authors review three main approaches to text modeling (structural, statistical and hybrid), their characteristics, pros and cons and applicability on different stages (knowledge extraction, storage and text generation) of solving problems in the field of analysis and generation of textual information.",
isbn="978-3-319-99316-4",
thanks = "rfbr-18-07-00032"
}

Abstract Methods of extracting knowledge in the analysis of large volumes of natural language texts are relevant for solving various problems in the field of analysis and generation of textual information, such as text analysis for extracting data, fact and semantics; presenting extracted information in a convenient for machine processing form (for example, ontology); classification and clustering texts, including thematic modeling; information retrieval (including thematic search, search based on the user model, ontology-based models, document sample based search); texts abstracting and annotating; developing of intelligent question-answering systems; generating texts of different types (fiction, marketing, weather forecasts etc.); as well as rewriting texts, preserving the meaning of the original text for presenting it to different target audiences. In order for such methods to work, it is necessary to construct and use models that adequately describe structural elements of the text on different levels (individual words, sentences, thematic text fragments), their characteristics and semantics, as well as relations between them, allowing to form higher-level structures. Such models should also take into account general characteristics of textual data: genre, purpose, target audience, scientific field and others. In this paper, authors review three main approaches to text modeling (structural, statistical and hybrid), their characteristics, pros and cons and applicability on different stages (knowledge extraction, storage and text generation) of solving problems in the field of analysis and generation of textual information.

2018 (5)

D. Litovkin, A. Anikin, M. Kultsova, E. Sarkisova (July 2018) Representation of WHAT-Knowledge Structures as Ontology Design Patterns. In 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA). pp. 1-6. doi bibtex

@INPROCEEDINGS{8633701, 
author={D. {Litovkin} and A. {Anikin} and M. {Kultsova} and E. {Sarkisova}}, 
booktitle={2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)}, 
title={Representation of WHAT-Knowledge Structures as Ontology Design Patterns}, 
year={2018}, 
volume={}, 
number={}, 
pages={1-6}, 
keywords={Unified modeling language;Ontologies;Taxonomy;Visualization;Mediation;OWL}, 
doi={10.1109/IISA.2018.8633701}, 
ISSN={}, 
month={July}, 
thanks = "rfbr-18-07-00032"}

M. Kultsova, D. Matyushechkin, A. Anikin (July 2018) Web-Service for Translation of Pictogram Messages into Russian Coherent Text. In 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA). pp. 1-5. doi bibtex

@INPROCEEDINGS{8633677, 
author={M. {Kultsova} and D. {Matyushechkin} and A. {Anikin}}, 
booktitle={2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)}, 
title={Web-Service for Translation of Pictogram Messages into Russian Coherent Text}, 
year={2018}, 
volume={}, 
number={}, 
pages={1-5}, 
keywords={Machine learning;Neural networks;Natural languages;Training;Servers;Python;Task analysis}, 
doi={10.1109/IISA.2018.8633677}, 
ISSN={}, 
month={July},
thanks = "rfbr-18-07-00032"}

M. Kultsova, A. Usov, A. Potseluico, A. Anikin (July 2018) An Ontological Representation of Interface Patterns in Context of Interface Adaptation for Users with Special Needs. In 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA). pp. 1-5. doi bibtex

@INPROCEEDINGS{8633682, 
author={M. {Kultsova} and A. {Usov} and A. {Potseluico} and A. {Anikin}}, 
booktitle={2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)}, 
title={An Ontological Representation of Interface Patterns in Context of Interface Adaptation for Users with Special Needs}, 
year={2018}, 
volume={}, 
number={}, 
pages={1-5}, 
keywords={Ontologies;Cognition;Adaptation models;Mobile applications;Databases;Engines;Software}, 
doi={10.1109/IISA.2018.8633682}, 
ISSN={}, 
month={July},
thanks = "rfbr-18-07-00032"}

Anton Anikin, Oleg Sychev (2018) Semantic treebanks and their uses for multi-level modelling of natural-language texts. Procedia Computer Science 145 pp. 64 - 71. doi web bibtex

@article{ANIKIN201864,
title = "Semantic treebanks and their uses for multi-level modelling of natural-language texts",
journal = "Procedia Computer Science",
volume = "145",
pages = "64 - 71",
year = "2018",
note = "Postproceedings of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2018 (Ninth Annual Meeting of the BICA Society), held August 22-24, 2018 in Prague, Czech Republic",
issn = "1877-0509",
doi = "10.1016/j.procs.2018.11.011",
url = "http://www.sciencedirect.com/science/article/pii/S1877050918322968",
author = "Anton Anikin and Oleg Sychev",
keywords = "Treebanks, Natural Language Processing, Ontology, Text Modelling",
thanks = "rfbr-18-07-00032"
}

Dmitrii Matyushechkin, Marina Kultsova, Anton Anikin (2018) Web-service for Translation Pictogrammes Sages into Coherent Text in Russian. Известия Волгоградского государственного технического университета 215 (5) pp. 30 - 36. web bibtex

@article{Matyushechkin2018,
title = "Web-service for Translation Pictogrammes Sages into Coherent Text in Russian",
journal = "Известия Волгоградского государственного технического университета",
number="5",
volume = "215",
pages = "30 - 36",
year = "2018",
issn = "1990-5297",
url = "https://elibrary.ru/item.asp?id=34991077",
author = "Dmitrii Matyushechkin, and Marina Kultsova, and Anton Anikin",
abstract="This article examines the implementation of web-service providing translation of pictogram messages into text messages in Russian. Also approaches to the decision of the given task are considered and results of development of methods of translation are presented. The developed web-service for the translation of pictogram messages into text messages can have a wide range of applications in the field of augmentative and alternative communication for people with mental and speech disorders. Also, this web service can be used by third-party software developers for people with disabilities, which will enable their programs to translate pictogram messages.",
thanks="rfbr-18-07-00032"
}

Abstract This article examines the implementation of web-service providing translation of pictogram messages into text messages in Russian. Also approaches to the decision of the given task are considered and results of development of methods of translation are presented. The developed web-service for the translation of pictogram messages into text messages can have a wide range of applications in the field of augmentative and alternative communication for people with mental and speech disorders. Also, this web service can be used by third-party software developers for people with disabilities, which will enable their programs to translate pictogram messages.

2017 (6)

M. Kultsova, D. Matyushechkin, A. Usov, S. Karpova, R. Romanenko (Aug 2017) Generation of pictograph sequences from the Russian text in the assistive mobile application for people with intellectual and developmental disabilities. In 2017 8th International Conference on Information, Intelligence, Systems Applications (IISA). pp. 1-4. doi bibtex

@INPROCEEDINGS{8316440, 
author={M. Kultsova and D. Matyushechkin and A. Usov and S. Karpova and R. Romanenko}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Generation of pictograph sequences from the Russian text in the assistive mobile application for people with intellectual and developmental disabilities}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-4}, 
abstract={This paper is devoted to a problem of correct translation of text in Russian to the sequence of pictograms for the mobile application “Travel and Communication Assistant” which supports the mobility and communication of people with intellectual and developmental disabilities. This application provides the possibility to such people to independently perform a known route (for example a route from home to the day care center, from home to the bakery, etc.) under the remote supervision of their caregivers and to communicate with them using text, voice and pictogram messages. A scheme of the process of translating a text in Russian into a sequence of pictograms was proposed and implemented as an extension of web service “Text2Picto” to the Russian language.}, 
keywords={handicapped aids;mobile computing;text analysis;Web services;pictograph sequences;Russian text;assistive mobile application;intellectual disabilities;developmental disabilities;Communication Assistant;mobility;pictogram messages;Text2Picto;Russian language;Databases;Speech;Mobile applications;Electronic mail;Web services;Natural languages;Color}, 
doi={10.1109/IISA.2017.8316440}, 
ISSN={}, 
month={Aug},}

Abstract This paper is devoted to a problem of correct translation of text in Russian to the sequence of pictograms for the mobile application “Travel and Communication Assistant” which supports the mobility and communication of people with intellectual and developmental disabilities. This application provides the possibility to such people to independently perform a known route (for example a route from home to the day care center, from home to the bakery, etc.) under the remote supervision of their caregivers and to communicate with them using text, voice and pictogram messages. A scheme of the process of translating a text in Russian into a sequence of pictograms was proposed and implemented as an extension of web service “Text2Picto” to the Russian language.

M. Kultsova, D. Matyushechkin, A. Usov, S. Karpova, A. Petrenko (Aug 2017) Assistive technology for complex support of children rehabilitation with autism spectrum disorder. In 2017 8th International Conference on Information, Intelligence, Systems Applications (IISA). pp. 1-5. doi bibtex

@INPROCEEDINGS{8316444, 
author={M. Kultsova and D. Matyushechkin and A. Usov and S. Karpova and A. Petrenko}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Assistive technology for complex support of children rehabilitation with autism spectrum disorder}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-5}, 
abstract={This paper is devoted to a problem of complex computer support of children rehabilitation with autism spectrum disorder. This goal is achieved due to the development of computer assistive technology which includes web system for online diagnostics, a mobile application for support of communications using PECS and interactive visual timetable. The proposed assistive technology was design and implemented in accordance with the requirements of specialists from Regional rehabilitation center for children with disabilities “Nadezhda” in Volzhsky city (Russia). At present, the developed web services and mobile applications are tested and evaluated in the rehabilitation center.}, 
keywords={handicapped aids;Internet;medical disorders;mobile computing;patient rehabilitation;Web services;autism spectrum disorder;computer assistive technology;web system;online diagnostics;mobile application;interactive visual timetable;Regional rehabilitation center;complex support;children rehabilitation;complex computer support;Nadezhda;Volzhsky city;web services;mobile applications;Autism;Electronic mail;Visualization;Assistive technology;Mobile applications;Monitoring;Servers}, 
doi={10.1109/IISA.2017.8316444}, 
ISSN={}, 
month={Aug},}

Abstract This paper is devoted to a problem of complex computer support of children rehabilitation with autism spectrum disorder. This goal is achieved due to the development of computer assistive technology which includes web system for online diagnostics, a mobile application for support of communications using PECS and interactive visual timetable. The proposed assistive technology was design and implemented in accordance with the requirements of specialists from Regional rehabilitation center for children with disabilities “Nadezhda” in Volzhsky city (Russia). At present, the developed web services and mobile applications are tested and evaluated in the rehabilitation center.

S. Regmi, B. K. Bal, M. Kultsova (Aug 2017) Analyzing facts and opinions in Nepali subjective texts. In 2017 8th International Conference on Information, Intelligence, Systems Applications (IISA). pp. 1-4. doi bibtex

@INPROCEEDINGS{8316445, 
author={S. Regmi and B. K. Bal and M. Kultsova}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Analyzing facts and opinions in Nepali subjective texts}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-4}, 
abstract={Subjectivity Analysis is a relatively new field of research for the Nepali language. It offers a challenging area which has not been adequately studied till date systematically. Limited works that have been conducted in Nepali include works primarily on polarity detection [7]. In this work, we propose a Supervised Machine Learning based framework for analyzing facts and opinions for Nepali subjective texts. We train three different models using three Supervised Machine Learning Classifiers: (Logistic Regression, Multinomial Naïve Bayes, and Support Vector Machine) and conduct a comparative study based on the metrics: Accuracy, Precision, Recall and F-Measure. Our results show that the task of analyzing subjective sentences and making a distinction between facts and opinions can be conducted with reasonable accuracies close to 70%.}, 
keywords={Bayes methods;learning (artificial intelligence);natural language processing;pattern classification;regression analysis;support vector machines;text analysis;Nepali subjective texts;Supervised Machine Learning Classifiers;Multinomial Naïve Bayes;Support Vector Machine;Subjectivity Analysis;Nepali language;opinion analysis;fact analysis;polarity detection;logistic regression;F-measure;subjective sentence analysis;Support vector machines;Machine learning algorithms;Feature extraction;Sentiment analysis;Logistics;Labeling;Computational modeling;Fact;Opinion;Subjectivity Classification;Machine Learning;TF-IDF;Logistic Regression;Multinomial Naïve Bayes;Support Vector Machine}, 
doi={10.1109/IISA.2017.8316445}, 
ISSN={}, 
month={Aug},}

Abstract Subjectivity Analysis is a relatively new field of research for the Nepali language. It offers a challenging area which has not been adequately studied till date systematically. Limited works that have been conducted in Nepali include works primarily on polarity detection [7]. In this work, we propose a Supervised Machine Learning based framework for analyzing facts and opinions for Nepali subjective texts. We train three different models using three Supervised Machine Learning Classifiers: (Logistic Regression, Multinomial Naïve Bayes, and Support Vector Machine) and conduct a comparative study based on the metrics: Accuracy, Precision, Recall and F-Measure. Our results show that the task of analyzing subjective sentences and making a distinction between facts and opinions can be conducted with reasonable accuracies close to 70%.

M. Kultsova, D. Litovkin, I. Zhukova, A. Dvoryankin (2017) Intelligent support of decision making in management of large-scale systems using case-based, rule-based and qualitative reasoning over ontologies. Communications in Computer and Information Science 754 pp. 331-349. Springer Verlag. doi web bibtex

@ARTICLE{Kultsova2017331,
author={Kultsova, M. and Litovkin, D. and Zhukova, I. and Dvoryankin, A.},
title={Intelligent support of decision making in management of large-scale systems using case-based, rule-based and qualitative reasoning over ontologies},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={331-349},
doi={10.1007/978-3-319-65551-2_24},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029418378&doi=10.1007%2f978-3-319-65551-2_24&partnerID=40&md5=6fa75ba7fa4e36ec9cda99997702f9eb},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The current trend in intelligent support of decision making is an integration of different knowledge representation models and reasoning mechanisms, it allows improving quality and efficiency of obtained decisions. In this paper, we present an ontology-based approach to intelligent support of decision making in the management of large-scale systems using case-based, rule-based and qualitative reasoning. A concept of the reasoning mechanisms integration implies that case-based reasoning (CBR) takes on the role of leading reasoning mechanism, while rule-based (RBR) and qualitative reasoning (QR) support the different phases of CBR-cycle - adaptation and revision phases respectively. The paper describes a modified CBR-cycle and ontological knowledge representation model which supports the proposed concept of reasoning integration. A formal qualitative model of decision making was developed for revision of case solution, it includes the following components: system state model, action model, and assessment model. An ontological representation of the qualitative model was proposed for integration with structural case model in an ontological knowledge base. Implementation of the proposed approach is illustrated by a number of examples of decision making support in various subject domains. © Springer International Publishing AG 2017.},
author_keywords={Intelligent support of decision making;  Knowledge intensive case based reasoning;  Ontological case representation;  Qualitative model},
keywords={Artificial intelligence;  Case based reasoning;  Integration;  Knowledge based systems;  Knowledge representation;  Large scale systems;  Ontology, Case representation;  Casebased reasonings (CBR);  Decision making support;  Intelligent support;  Ontological representation;  Qualitative model;  Qualitative reasoning;  Reasoning mechanism, Decision making},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

Abstract The current trend in intelligent support of decision making is an integration of different knowledge representation models and reasoning mechanisms, it allows improving quality and efficiency of obtained decisions. In this paper, we present an ontology-based approach to intelligent support of decision making in the management of large-scale systems using case-based, rule-based and qualitative reasoning. A concept of the reasoning mechanisms integration implies that case-based reasoning (CBR) takes on the role of leading reasoning mechanism, while rule-based (RBR) and qualitative reasoning (QR) support the different phases of CBR-cycle - adaptation and revision phases respectively. The paper describes a modified CBR-cycle and ontological knowledge representation model which supports the proposed concept of reasoning integration. A formal qualitative model of decision making was developed for revision of case solution, it includes the following components: system state model, action model, and assessment model. An ontological representation of the qualitative model was proposed for integration with structural case model in an ontological knowledge base. Implementation of the proposed approach is illustrated by a number of examples of decision making support in various subject domains. © Springer International Publishing AG 2017.

M. Kultsova, A. Potseluico, I. Zhukova, A. Skorikov, R. Romanenko (2017) A two-phase method of user interface adaptation for people with special needs. Communications in Computer and Information Science 754 pp. 805-821. Springer Verlag. doi web bibtex

@ARTICLE{Kultsova2017805,
author={Kultsova, M. and Potseluico, A. and Zhukova, I. and Skorikov, A. and Romanenko, R.},
title={A two-phase method of user interface adaptation for people with special needs},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={805-821},
doi={10.1007/978-3-319-65551-2_58},
note={cited By 0},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029459724&doi=10.1007%2f978-3-319-65551-2_58&partnerID=40&md5=64685c530e95317bf3a4db61519e1f7a},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The paper is devoted to a problem of increasing accessibility of mobile applications for people with disabilities, that requires the creation of specialized adaptive user interfaces. A knowledge-intensive approach to the design of adaptive user interface was proposed on the basis of integration of ontological user modeling and design pattern approach. An ontological model of the adaptive user interface and interface pattern model were developed as well as an ontological knowledge base and pattern database. A two-phase method of user interface adaptation for people with special needs based on the ontological user model, rule-based reasoning over ontology and interface design patterns was developed. The method was implemented in a software tool for user interface developers. The application of the proposed approach is illustrated by a number of examples of user interface design and adaptation for people with special needs. © Springer International Publishing AG 2017.},
author_keywords={Adaptive user interface;  Assistive technologies;  Interface patterns;  Mobile applications;  Ontological user modeling},
keywords={Knowledge based systems;  Mobile computing;  Mobile telecommunication systems;  Ontology;  Phase interfaces, Adaptive user interface;  Assistive technology;  Interface patterns;  Mobile applications;  User Modeling, User interfaces},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

Abstract The paper is devoted to a problem of increasing accessibility of mobile applications for people with disabilities, that requires the creation of specialized adaptive user interfaces. A knowledge-intensive approach to the design of adaptive user interface was proposed on the basis of integration of ontological user modeling and design pattern approach. An ontological model of the adaptive user interface and interface pattern model were developed as well as an ontological knowledge base and pattern database. A two-phase method of user interface adaptation for people with special needs based on the ontological user model, rule-based reasoning over ontology and interface design patterns was developed. The method was implemented in a software tool for user interface developers. The application of the proposed approach is illustrated by a number of examples of user interface design and adaptation for people with special needs. © Springer International Publishing AG 2017.

A. Anikin, D. Litovkin, M. Kultsova, E. Sarkisova, T. Petrova (2017) Ontology visualization: Approaches and software tools for visual representation of large ontologies in learning. Communications in Computer and Information Science 754 pp. 133-149. Springer Verlag. doi web bibtex

@ARTICLE{Anikin2017133,
author={Anikin, A. and Litovkin, D. and Kultsova, M. and Sarkisova, E. and Petrova, T.},
title={Ontology visualization: Approaches and software tools for visual representation of large ontologies in learning},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={133-149},
doi={10.1007/978-3-319-65551-2_10},
note={cited By 0; Конференция 2nd Conference on Creativity in Intelligent Technologies and Data Science, CIT and DS 2017 ; Дата конференции: с 12 September 2017 по 14 September 2017;  Код конференции:197189},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029446521&doi=10.1007%2f978-3-319-65551-2_10&partnerID=40&md5=afe223b4bf23023f708f73a0259ee0ae},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation; Volgograd State Socio-Pedagogical University, Volgograd, Russian Federation},
abstract={In this paper, we address the issue of large ontologies visualization for learning. The ontologies can be used to improve the efficiency of the learning when the learner explores a new subject domain and needs its conceptual model. The ontologies can help to overview this new subject domain, to better understand current knowledge, the knowledge that should be got, the subject domain structure, main concepts, relationships between them and relevant information resources. However with increasing the complexity of domain structure, the number of concepts and relationships, it becomes more difficult to overview and understand conceptual model represented with the ontology. We review the approaches to ontology visualization and their implementation in the software tools that can help to resolve this issue. © Springer International Publishing AG 2017.},
author_keywords={Ontology;  Ontology visualization;  Semantic web},
keywords={Computer software;  Semantic Web;  Visualization, Conceptual model;  Domain structure;  Information resource;  Ontology visualizations;  Visual representations, Ontology},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
sponsors={},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

Abstract In this paper, we address the issue of large ontologies visualization for learning. The ontologies can be used to improve the efficiency of the learning when the learner explores a new subject domain and needs its conceptual model. The ontologies can help to overview this new subject domain, to better understand current knowledge, the knowledge that should be got, the subject domain structure, main concepts, relationships between them and relevant information resources. However with increasing the complexity of domain structure, the number of concepts and relationships, it becomes more difficult to overview and understand conceptual model represented with the ontology. We review the approaches to ontology visualization and their implementation in the software tools that can help to resolve this issue. © Springer International Publishing AG 2017.

2016 (6)

Marina Kultsova, Anastasiya Potseluico, Anton Anikin, Roman Romanenko (Nov 2016) An Ontology Based Adaptation of User Interface for People with Special Needs. In 2016 IEEE Artificial Intelligence and Natural Language Conference (AINL). pp. 92-94. bibtex

@INPROCEEDINGS{7891861, 
booktitle={2016 IEEE Artificial Intelligence and Natural Language Conference (AINL)}, 
author = {Kultsova, Marina and Potseluico, Anastasiya and Anikin, Anton and Romanenko, Roman},
title={An Ontology Based Adaptation of User Interface for People with Special Needs}, 
year={2016}, 
pages={92-94}, 
keywords={Artificial intelligence;Business intelligence;Natural language processing;Organizations;Seminars;Speech}, 
month={Nov},}

M. Kultsova, R. Rudnev, A. Anikin, I. Zhukova (July 2016) An ontology-based approach to intelligent support of decision making in waste management. In 2016 7th International Conference on Information, Intelligence, Systems Applications (IISA). pp. 1-6. doi bibtex

@INPROCEEDINGS{7785401, 
author={M. Kultsova and R. Rudnev and A. Anikin and I. Zhukova}, 
booktitle={2016 7th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={An ontology-based approach to intelligent support of decision making in waste management}, 
year={2016}, 
pages={1-6}, 
keywords={decision making;decision support systems;environmental science computing;inference mechanisms;ontologies (artificial intelligence);waste management;contemporary technologies;domain knowledge representation;intelligent decision making support;knowledge-based approach;ontology-based approach;rule-based reasoning;waste management system;Cognition;Decision making;Electronic mail;Knowledge based systems;Ontologies;Recycling;Waste management}, 
doi={10.1109/IISA.2016.7785401}, 
month={July},}

M. Kultsova, A. Potseluico, A. Anikin, R. Romanenko (July 2016) An ontological user model for automated generation of adaptive interface for users with special needs. In 2016 7th International Conference on Information, Intelligence, Systems Applications (IISA). pp. 1-6. doi bibtex

@INPROCEEDINGS{7785411, 
author={M. Kultsova and A. Potseluico and A. Anikin and R. Romanenko}, 
booktitle={2016 7th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={An ontological user model for automated generation of adaptive interface for users with special needs}, 
year={2016}, 
pages={1-6}, 
keywords={diseases;handicapped aids;inference mechanisms;ontologies (artificial intelligence);user modelling;SWLR-rules;application interface domain ontology;automated adaptive interface generation;disease ontology;interface adaptation;ischemic stroke;meta-ontology;ontological user model;rule-based reasoning;user device domain ontology;user disability domain ontology;Adaptation models;Cognition;Diseases;Mobile communication;Ontologies;User interfaces;Visualization}, 
doi={10.1109/IISA.2016.7785411}, 
month={July},}

M. Kultsova, A. Anikin, D. Litovkin (February 2016) An Ontology-Based Approach to Collaborative Development of Domain Information Space. In Proceedings of the 12th International Conference on Educational Technologies (EDUTE`16), Proceedings of the 10th International Conference on Business Administration (ICBA`16), Barcelona, Spain, February 13-15, 2016. pp. 13-19. web bibtex

@INPROCEEDINGS{WSEAS2016, 
author={M. Kultsova and A. Anikin and D. Litovkin}, 
booktitle={Proceedings of the 12th International Conference on Educational Technologies (EDUTE`16), Proceedings of the 10th International Conference on Business Administration (ICBA`16), Barcelona, Spain, February 13-15, 2016}, 
title={An Ontology-Based Approach to Collaborative Development of Domain Information Space}, 
year={2016}, 
pages={13-19}, 
month={February},
url={http://www.wseas.us/e-library/conferences/2016/barcelona/EDBA/EDBA-01.pdf},
}

Marina Kultsova, Roman Romanenko, Irina Zhukova, Andrey Usov, Nikita Penskoy, Tatiana Potapova (2016) Assistive Mobile Application for Support of Mobility and Communication of People with IDD. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. pp. 1073–1076. ACM. New York, NY, USA. doi web bibtex

@inproceedings{Kultsova:2016:AMA:2957265.2965003,
 author = {Kultsova, Marina and Romanenko, Roman and Zhukova, Irina and Usov, Andrey and Penskoy, Nikita and Potapova, Tatiana},
 title = {Assistive Mobile Application for Support of Mobility and Communication of People with IDD},
 booktitle = {Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct},
 series = {MobileHCI '16},
 year = {2016},
 isbn = {978-1-4503-4413-5},
 location = {Florence, Italy},
 pages = {1073--1076},
 numpages = {4},
 url = {http://doi.acm.org/10.1145/2957265.2965003},
 doi = {10.1145/2957265.2965003},
 acmid = {2965003},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {adaptive user interface, assistive technologies, intellectual and developmental disabilities, mobile applications, special needs assessment},
}

Anton Anikin, Dmitry Litovkin, Marina Kultsova, Elena Sarkisova (2016) Ontology-Based Collaborative Development of Domain Information Space for Learning and Scientific Research. In Knowledge Engineering and Semantic Web: 7th International Conference, KESW 2016, Prague, Czech Republic, September 21-23, 2016, Proceedings. pp. 301–315. Springer International Publishing. Cham. doi web bibtex

@Inbook{Anikin2016,
author="Anikin, Anton
and Litovkin, Dmitry
and Kultsova, Marina
and Sarkisova, Elena",
editor="Ngonga Ngomo, Axel-Cyrille
and K{\v{r}}emen, Petr",
title="Ontology-Based Collaborative Development of Domain Information Space for Learning and Scientific Research",
bookTitle="Knowledge Engineering and Semantic Web: 7th International Conference, KESW 2016, Prague, Czech Republic, September 21-23, 2016, Proceedings",
year="2016",
publisher="Springer International Publishing",
address="Cham",
pages="301--315",
isbn="978-3-319-45880-9",
doi="10.1007/978-3-319-45880-9_23",
url="http://dx.doi.org/10.1007/978-3-319-45880-9_23"
}

2015 (4)

M. Kultsova, A. Anikin, I. Zhukova (July 2015) Ontology-based method of electronic learning resources retrieval and integration. In 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA). pp. 1-6. doi bibtex

@INPROCEEDINGS{7388112, 
author={M. Kultsova and A. Anikin and I. Zhukova}, 
booktitle={2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)}, 
title={Ontology-based method of electronic learning resources retrieval and integration}, 
year={2015}, 
pages={1-6}, 
keywords={C++ language;computer aided instruction;distributed processing;information retrieval;ontologies (artificial intelligence);C++ language;Volgograd State Technical University;distributed learning resources;electronic learning resources integration;electronic learning resources retrieval;ontology-based method;personal learning collections;programming languages;Cognition;Complexity theory;Electronic learning;Erbium;Metadata;Ontologies;Semantics}, 
doi={10.1109/IISA.2015.7388112}, 
month={July},}

Jan Dekelver, Marina Kultsova, Olga Shabalina, Julia Borblik, Alexander Pidoprigora, Roman Romanenko (2015) Design of Mobile Applications for People with Intellectual Disabilities. In Creativity in Intelligent, Technologies and Data Science: First Conference, CIT&DS 2015, Volgograd, Russia, September 15–17, 2015, Proceedings. pp. 823–836. Springer International Publishing. Cham. doi web bibtex

@Inbook{Dekelver2015,
author="Dekelver, Jan
and Kultsova, Marina
and Shabalina, Olga
and Borblik, Julia
and Pidoprigora, Alexander
and Romanenko, Roman",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Shabalina, Olga",
title="Design of Mobile Applications for People with Intellectual Disabilities",
bookTitle="Creativity in Intelligent, Technologies and Data Science: First Conference, CIT{\&}DS 2015, Volgograd, Russia, September 15--17, 2015, Proceedings",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="823--836",
isbn="978-3-319-23766-4",
doi="10.1007/978-3-319-23766-4_65",
url="http://dx.doi.org/10.1007/978-3-319-23766-4_65"
}

Marina Kultsova, Anton Anikin, Irina Zhukova, Alexander Dvoryankin (2015) Ontology-Based Learning Content Management System in Programming Languages Domain. In Creativity in Intelligent, Technologies and Data Science: First Conference, CIT&DS 2015, Volgograd, Russia, September 15–17, 2015, Proceedings. pp. 767–777. Springer International Publishing. Cham. doi web bibtex

@Inbook{Kultsova2015,
author="Kultsova, Marina
and Anikin, Anton
and Zhukova, Irina
and Dvoryankin, Alexander",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Shabalina, Olga",
title="Ontology-Based Learning Content Management System in Programming Languages Domain",
bookTitle="Creativity in Intelligent, Technologies and Data Science: First Conference, CIT{\&}DS 2015, Volgograd, Russia, September 15--17, 2015, Proceedings",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="767--777",
isbn="978-3-319-23766-4",
doi="10.1007/978-3-319-23766-4_61",
url="http://dx.doi.org/10.1007/978-3-319-23766-4_61"
}

Irina Zhukova, Marina Kultsova, Dmitry Litovkin, Dmitry Kozlov (2015) Generation of OWL Ontologies from Confinement Models. In Creativity in Intelligent, Technologies and Data Science: First Conference, CIT&DS 2015, Volgograd, Russia, September 15–17, 2015, Proceedings. pp. 191–203. Springer International Publishing. Cham. doi web bibtex

@Inbook{Zhukova2015,
author="Zhukova, Irina
and Kultsova, Marina
and Litovkin, Dmitry
and Kozlov, Dmitry",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Shabalina, Olga",
title="Generation of OWL Ontologies from Confinement Models",
bookTitle="Creativity in Intelligent, Technologies and Data Science: First Conference, CIT{\&}DS 2015, Volgograd, Russia, September 15--17, 2015, Proceedings",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="191--203",
isbn="978-3-319-23766-4",
doi="10.1007/978-3-319-23766-4_16",
url="http://dx.doi.org/10.1007/978-3-319-23766-4_16"
}

2014 (4)

Peter Wriggers, Marina Kultsova, Alexander Kapysh, Anton Kultsov, Irina Zhukova (2014) Intelligent Decision Support System for River Floodplain Management. In Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings. pp. 195–213. Springer International Publishing. Cham. doi web bibtex

@Inbook{Wriggers2014,
author="Wriggers, Peter
and Kultsova, Marina
and Kapysh, Alexander
and Kultsov, Anton
and Zhukova, Irina",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Iijima, Tadashi",
title="Intelligent Decision Support System for River Floodplain Management",
bookTitle="Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="195--213",
isbn="978-3-319-11854-3",
doi="10.1007/978-3-319-11854-3_18",
url="http://dx.doi.org/10.1007/978-3-319-11854-3_18"
}

Anton Anikin, Marina Kultsova, Irina Zhukova, Natalia Sadovnikova, Dmitry Litovkin (2014) Knowledge Based Models and Software Tools for Learning Management in Open Learning Network. In Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings. pp. 156–171. Springer International Publishing. Cham. doi web bibtex

@Inbook{Anikin2014,
author="Anikin, Anton
and Kultsova, Marina
and Zhukova, Irina
and Sadovnikova, Natalia
and Litovkin, Dmitry",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Iijima, Tadashi",
title="Knowledge Based Models and Software Tools for Learning Management in Open Learning Network",
bookTitle="Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="156--171",
isbn="978-3-319-11854-3",
doi="10.1007/978-3-319-11854-3_15",
url="http://dx.doi.org/10.1007/978-3-319-11854-3_15"
}

Irina Zhukova, Marina Kultsova, Mikhail Navrotsky, Alexander Dvoryankin (2014) Intelligent Support of Decision Making in Human Resource Management Using Case-Based Reasoning and Ontology. In Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings. pp. 172–184. Springer International Publishing. Cham. doi web bibtex

@Inbook{Zhukova2014,
author="Zhukova, Irina
and Kultsova, Marina
and Navrotsky, Mikhail
and Dvoryankin, Alexander",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Iijima, Tadashi",
title="Intelligent Support of Decision Making in Human Resource Management Using Case-Based Reasoning and Ontology",
bookTitle="Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="172--184",
isbn="978-3-319-11854-3",
doi="10.1007/978-3-319-11854-3_16",
url="http://dx.doi.org/10.1007/978-3-319-11854-3_16"
}

Dmitry Litovkin, Irina Zhukova, Marina Kultsova, Natalia Sadovnikova, Alexander Dvoryankin (2014) Adaptive Testing Model and Algorithms for Learning Management System. In Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings. pp. 87–99. Springer International Publishing. Cham. doi web bibtex

@Inbook{Litovkin2014,
author="Litovkin, Dmitry
and Zhukova, Irina
and Kultsova, Marina
and Sadovnikova, Natalia
and Dvoryankin, Alexander",
editor="Kravets, Alla
and Shcherbakov, Maxim
and Kultsova, Marina
and Iijima, Tadashi",
title="Adaptive Testing Model and Algorithms for Learning Management System",
bookTitle="Knowledge-Based Software Engineering: 11th Joint Conference, JCKBSE 2014, Volgograd, Russia, September 17-20, 2014. Proceedings",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="87--99",
isbn="978-3-319-11854-3",
doi="10.1007/978-3-319-11854-3_9",
url="http://dx.doi.org/10.1007/978-3-319-11854-3_9"
}

2008 (1)

Peter Wriggers, Marina Siplivaya, Irina Joukova, Roman Slivin (2008) Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning. Engineering with Computers 24 (4) pp. 383–404. doi web bibtex

@Article{Wriggers2008,
author="Wriggers, Peter
and Siplivaya, Marina
and Joukova, Irina
and Slivin, Roman",
title="Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning",
journal="Engineering with Computers",
year="2008",
volume="24",
number="4",
pages="383--404",
abstract="The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology. In this paper the automated knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.",
issn="1435-5663",
doi="10.1007/s00366-007-0079-5",
url="http://dx.doi.org/10.1007/s00366-007-0079-5"
}

Abstract The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology. In this paper the automated knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.

2007 (2)

Peter Wriggers, Marina Siplivaya, Irina Joukova, Roman Slivin (aug 2007) Intelligent Support of Engineering Analysis Using Ontology and Case-based Reasoning. Eng. Appl. Artif. Intell. 20 (5) pp. 709–720. Pergamon Press, Inc.. Tarrytown, NY, USA. doi web bibtex

@article{Wriggers:2007:ISE:1265605.1265719,
 author = {Wriggers, Peter and Siplivaya, Marina and Joukova, Irina and Slivin, Roman},
 title = {Intelligent Support of Engineering Analysis Using Ontology and Case-based Reasoning},
 journal = {Eng. Appl. Artif. Intell.},
 issue_date = {August, 2007},
 volume = {20},
 number = {5},
 month = aug,
 year = {2007},
 issn = {0952-1976},
 pages = {709--720},
 numpages = {12},
 url = {http://dx.doi.org/10.1016/j.engappai.2006.12.002},
 doi = {10.1016/j.engappai.2006.12.002},
 acmid = {1265719},
 publisher = {Pergamon Press, Inc.},
 address = {Tarrytown, NY, USA},
 keywords = {Case-based reasoning, Engineering analysis, Intelligent support, Ontology},
}

P. Wriggers, M. Siplivaya, I. Zhukova, A. Kapysh, A. Kultsov (2007) Integration of a case-based reasoning and an ontological knowledge base in the system of intelligent support of finite element analysis. Computer Assisted Mechanics and Engineering Sciences Vol. 14, No. 4 pp. 753–765. bibtex

@article{WSZKK2007,
  author="P. Wriggers and M. Siplivaya and I. Zhukova and A. Kapysh and A. Kultsov",
  title = "Integration of a case-based reasoning and an ontological knowledge base in the system of intelligent support of finite element analysis",
  journal = "Computer Assisted Mechanics and Engineering Sciences",
  volume = "Vol. 14, No. 4",
  year = "2007",
  pages = "753--765",
}