Volgograd State University, Mathematical physics, 1988, Volgograd, Russia
PhD in Computer Science, 1998, Chair of CAD/CAE Systems, Volgograd State Technical University, Volgograd, Russia
In-depth 20+ years expertise in teaching and scientific researches in the area of Artificial Intelligence and it applications, including knowledge engineering, intelligent data analysis, automated reasoning, knowledge representation, Semantic Web technologies, intelligent support of decision making and human-computer interaction. Experienced as a team leader and member of various international research and educational projects. Result-driven, strong analytic skills, focused on problem solving, a team player with critical thinking and good communication skills. An author and co-author of more than 70 research papers, 7 patents and 10 university courses.
1988-present:
Volgograd State Technical University, Volgograd, Russia
Associate Professor, Chair of Software Engineering, Computer Science Faculty
Research activity:
As a head and a member of research groups carried out 3 research projects in the areas of intelligent decision making and knowledge engineering under financial support from RFBR
Created and headed the “Intelligent decision making” and “Simulating HCI for special needs” research groups, participated in PC of international conferences (IADIS, JCKBSE,I2T, IISA, CIT&DS).
5 DAAD research fellowships in Leibniz University Hanover (2000, 2002, 2004, 2006, 2008).
Developed intelligent decision making models, methods and software tools in various domains (engineering analysis, environmental management, human resource management, learning management).
Authored 16 papers listed in Scopus and Web of Science and 56 listed in Russian SCI.
PC Member and reviewer of papers for conference JCKBSE and CIT&DS, Volume editor of Communications in Computer and Information Science. Knowledge-Based Software Engineering, volume 466, Springer, 2014 and Creativity in Intelligent Technologies & Data Science, volume 535, 2015.
Teaching activity:
Supervised and co-promoted 4 PhD students (promoted in 2006, 2011, 2013, 2014), 12 master students and a plenty of bachelors.
Developed curriculum and courses in “Artificial Intelligence”, “Knowledge Based Systems”, “Knowledge Engineering”, “Intelligent Decision Making”, “Applied System Analysis”.
2000, 2002, 2004, 2006, 2008-2009:
Leibniz University Hanover, Germany
Guest researcher, IBNM, IKM
5 DAAD research fellowships in the area of intelligent support of finite element analysis under supervising Prof. P. Wriggers.
Participated in EU Project RAMWASS (development of intelligent decision support system in Elbe river floodplain management).
2004-2009:
Volgograd State University of Architecture and Civil Engineering
Guest Lecturer
As a contact person participated in Tempus Project (2005-2008).
Performed teaching activity, courses “Artificial Intelligence”, “Semantic Web Technologies”, “Mathematical Modeling”.
Participated as a guest lecturer in organization of summer schools for students of MacMaster University, Canada, course “Engineering analysis using FEM” (2005-2008).
RFBR Project 15-07-03541 “Intelligent support of decision making in management of large scale systems based on integration of different reasoning types on ontological knowledge” (2015 – 2017).
RamWass EU Project 037081 Integrated decision support system for risk assessment and management of the water-sediment-soil system at river basin scale in fluvial ecosystems (2007 – 2009).
Tempus Gemeinsames Europäisches Projekt JEP_26211_2005 “Bachelor-/Master-Studium in Umwelttechnik” (2005-2008).
RFBR Project 05-08-17930 Intelligent Support of Engineering Analysis Based on Ontologies, Qualitative Reasoning and Case-Based Reasoning (2005 – 2007).
RFBR Project 13-07-00219 “Intelligent support of strategic planning based on integration of cognitive and ontological models” (2013 – 2015).
English – fluent
German – intermediate
Russian – native
An author and co-author of more than 70 research papers, 7 patents and 10 university courses, including 16 papers listed in Scopus and Web of Science and 56 listed in Russian SCI.
2017 (3)
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},
note={cited By 0},
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",
}
Assoc. Prof., PhD
