An ontology-based approach to intelligent support of decision making in waste management
In this paper a concept of intelligent support of decision making in waste management using knowl... more In this paper a concept of intelligent support of decision making in waste management using knowledge-based approach is presented, which is a promising way to increase efficiency of waste management system in the cities. Analysis of the domain of waste management shows that the appropriate support of decision making can be implemented using contemporary technologies of artificial intelligent such as rule-based reasoning and ontology. In the paper a general scheme of the integration of this reasoning mechanism and ontology is suggested, as well the problems of domain knowledge representation are considered. Implementation of a prototype of intelligent decision support system in waste management using rule-based reasoning and ontology is described.
Ontology-based method of electronic learning resources retrieval and integration
This paper presents an ontology-based method of electronic learning resources retrieval and integ... more This paper presents an ontology-based method of electronic learning resources retrieval and integration to create the personal learning collections. To implement proposed ontology-based approach the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) integrated via meta-ontology was elaborated as well as the semantic rules and algorithms for retrieval and integration of distributed learning resources into personal collections. Developed method and algorithms were implemented in form of application for creating the personal learning collections. Suggested approach was applied for creation of personal collections for the course "Programming Languages. C++" in Volgograd State Technical University.
Domain ontologies that can solve various tasks using its concepts and determine fault reason for ... more Domain ontologies that can solve various tasks using its concepts and determine fault reason for students’ answers may serve as a good basis for creating for a testing system with extensive explanatory abilities. But capabilities of modern ontological reasoners may not be enough for this kind of task. In this study, we developed and tested an ontology able to build execution trace for the given algorithm containing sequences and alternatives and find fault reasons for incorrect traces. The study also showed problems with the used reasoner that hinder the developed ontology from becoming fully effective.
Модели и инструментальные средства интеграции распределенных ресурсов в открытых образовательных сетях
In this paper, proposed ontology-based models and software tools for annotation of electronic edu... more In this paper, proposed ontology-based models and software tools for annotation of electronic educational resources and creating of the personal educational collections.
Intelligent tutoring systems have become increasingly common in assisting students but are often ... more 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 classi...
Frontiers in Artificial Intelligence and Applications, 2021
Developing algorithms using control structures and understanding their building blocks are essent... more 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 kin...
This paper is devoted to a problem of creating the domain information space for the purpose of fu... more This paper is devoted to a problem of creating the domain information space for the purpose of further information retrieval and reuse in different subject domains. We propose an ontology-based approach to collaborative development of the domain information space using the personal human cognitive spaces. In framework of the proposed approach the information space ontology is constructed and the algorithm for generation of domain information space is developed on the base of personal cognitive spaces using reasoning on ontology. The application of the proposed approach is illustrated by the example of the information space construction for subject domain of programming languages.
Methods of extracting knowledge in the analysis of large volumes of natural language texts are re... more 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.
Communications in Computer and Information Science, 2014
Nowadays there is a wide variety of open informational and learning resources on the Internet, in... more Nowadays there is a wide variety of open informational and learning resources on the Internet, in local universities networks and other locations that can be used for the e-learning. These resources of the heterogeneous nature with different level of complexity and comprehension of knowledge content can satisfy the requirements of different learning groups and individuals. The problem is to find resources that achieve the learning objectives, current background and other requirements of the learner out of a great number of available resources, and to provide the learner a way to achieve required learning outcomes. This paper presents an ontology-based approach to create the personal collections of learning resources. To manage the learning process the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) is elaborated as well as the ontology reasoning rules and algorithms for retrieval and integration of distributed learning resources into personal collections. In the framework of considered approach the software architecture and web application for creating the personal collections of learning resources have been developed. Suggested approach was applied to create personal collections for the course Programming Languages. C++ in Volgograd State Technical University.
An ontology-based approach to intelligent support of decision making in waste management
In this paper a concept of intelligent support of decision making in waste management using knowl... more In this paper a concept of intelligent support of decision making in waste management using knowledge-based approach is presented, which is a promising way to increase efficiency of waste management system in the cities. Analysis of the domain of waste management shows that the appropriate support of decision making can be implemented using contemporary technologies of artificial intelligent such as rule-based reasoning and ontology. In the paper a general scheme of the integration of this reasoning mechanism and ontology is suggested, as well the problems of domain knowledge representation are considered. Implementation of a prototype of intelligent decision support system in waste management using rule-based reasoning and ontology is described.
Ontology-based method of electronic learning resources retrieval and integration
This paper presents an ontology-based method of electronic learning resources retrieval and integ... more This paper presents an ontology-based method of electronic learning resources retrieval and integration to create the personal learning collections. To implement proposed ontology-based approach the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) integrated via meta-ontology was elaborated as well as the semantic rules and algorithms for retrieval and integration of distributed learning resources into personal collections. Developed method and algorithms were implemented in form of application for creating the personal learning collections. Suggested approach was applied for creation of personal collections for the course "Programming Languages. C++" in Volgograd State Technical University.
Domain ontologies that can solve various tasks using its concepts and determine fault reason for ... more Domain ontologies that can solve various tasks using its concepts and determine fault reason for students’ answers may serve as a good basis for creating for a testing system with extensive explanatory abilities. But capabilities of modern ontological reasoners may not be enough for this kind of task. In this study, we developed and tested an ontology able to build execution trace for the given algorithm containing sequences and alternatives and find fault reasons for incorrect traces. The study also showed problems with the used reasoner that hinder the developed ontology from becoming fully effective.
Модели и инструментальные средства интеграции распределенных ресурсов в открытых образовательных сетях
In this paper, proposed ontology-based models and software tools for annotation of electronic edu... more In this paper, proposed ontology-based models and software tools for annotation of electronic educational resources and creating of the personal educational collections.
Intelligent tutoring systems have become increasingly common in assisting students but are often ... more 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 classi...
Frontiers in Artificial Intelligence and Applications, 2021
Developing algorithms using control structures and understanding their building blocks are essent... more 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 kin...
This paper is devoted to a problem of creating the domain information space for the purpose of fu... more This paper is devoted to a problem of creating the domain information space for the purpose of further information retrieval and reuse in different subject domains. We propose an ontology-based approach to collaborative development of the domain information space using the personal human cognitive spaces. In framework of the proposed approach the information space ontology is constructed and the algorithm for generation of domain information space is developed on the base of personal cognitive spaces using reasoning on ontology. The application of the proposed approach is illustrated by the example of the information space construction for subject domain of programming languages.
Methods of extracting knowledge in the analysis of large volumes of natural language texts are re... more 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.
Communications in Computer and Information Science, 2014
Nowadays there is a wide variety of open informational and learning resources on the Internet, in... more Nowadays there is a wide variety of open informational and learning resources on the Internet, in local universities networks and other locations that can be used for the e-learning. These resources of the heterogeneous nature with different level of complexity and comprehension of knowledge content can satisfy the requirements of different learning groups and individuals. The problem is to find resources that achieve the learning objectives, current background and other requirements of the learner out of a great number of available resources, and to provide the learner a way to achieve required learning outcomes. This paper presents an ontology-based approach to create the personal collections of learning resources. To manage the learning process the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) is elaborated as well as the ontology reasoning rules and algorithms for retrieval and integration of distributed learning resources into personal collections. In the framework of considered approach the software architecture and web application for creating the personal collections of learning resources have been developed. Suggested approach was applied to create personal collections for the course Programming Languages. C++ in Volgograd State Technical University.
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Papers by Anton Anikin