Class-based n-gram models of natural language
Computational Linguistics
A maximum entropy approach to natural language processing
Computational Linguistics
A Review of Statistical Language Processing Techniques
Artificial Intelligence Review
Journal of Computers in Mathematics and Science Teaching
Knowledge Representation and Management in ACTIVEMATH
Annals of Mathematics and Artificial Intelligence
A conceptual map model for developing intelligent tutoring systems
Computers & Education
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites
Computational Linguistics
On document relevance and lexical cohesion between query terms
Information Processing and Management: an International Journal
On the reliability of information retrieval metrics based on graded relevance
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Lexical cohesion and term proximity in document ranking
Information Processing and Management: an International Journal
ZOSMAT: Web-based intelligent tutoring system for teaching-learning process
Expert Systems with Applications: An International Journal
Advanced Geometry Tutor: An intelligent tutor that teaches proof-writing with construction
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Corpus-based knowledge representation
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Case-Based student modeling using concept maps
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
AutoTutor: an intelligent tutoring system with mixed-initiative dialogue
IEEE Transactions on Education
Self-assessment in a feasible, adaptive web-based testing system
IEEE Transactions on Education
A majority density approach for developing testing and diagnostic systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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This paper argues that the educational support systems can give a meaning to an educational content semantically, and an answer has been sought to the question of ''what should be taught to students'' in the field of intelligent tutoring systems. With reference this aim, a system, which automatically detects the concepts to be learned by students, has been designed. The developed system uses the statistical language models together with conceptual map modeling as a student model to extract the minimal set of learning concepts within an educational content. In the study, ten corpora have been generated as a learning domain, which consist of two different subjects in mathematics. For each subject, five distinct chapters have been quoted from the books written by various authors. After extracting the candidate concepts from the given content, the system checks to clarify whether these candidates are in a dictionary within postprocessing. The dictionary consists of approximately 9500 technical terms related to the learning domain. The system performance has also been analyzed using Recall, Precision and F-measure scores. The results indicate that the postprocessing step increases precision with a small loss of recall.