@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} }

@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} }

@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} }

@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} }

@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}

} @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}

} @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.}

}

@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.}

}

@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” }

@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” }

@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}, }

@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}, }

@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}, }

@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},}

@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}, }

@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}, }

@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},}

@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},}

@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},}

@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” }

@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” }

@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” }

@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” }

@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” }

@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” }

@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” }

@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” }

@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",

}

@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}, }

@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” }

@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”} @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”} @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”}

@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” }

@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},}

@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},}

@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},}