Information Retrieval
Reusable learning objects: a survey of LOM-based repositories
Proceedings of the tenth ACM international conference on Multimedia
Automatic Extraction of Ontologies from Teaching Document Metadata
ICCE '02 Proceedings of the International Conference on Computers in Education
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
On Automated Lesson Construction from Electronic Textbooks
IEEE Transactions on Knowledge and Data Engineering
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Domain Ontology for Personalized E-Learning in Educational Systems
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Learning to identify single-snippet answers to definition questions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Definition Extraction with Balanced Random Forests
GoTAL '08 Proceedings of the 6th international conference on Advances in Natural Language Processing
Towards the automatic extraction of definitions in Slavic
ACL '07 Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies
KeyPhrase Extraction Tool (KET) for Semantic Metadata Annotation of Learning Materials
ICSPS '09 Proceedings of the 2009 International Conference on Signal Processing Systems
Extraction of definitions using grammar-enhanced machine learning
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Personalising learning through prerequisite structures derived from concept maps
ICWL'07 Proceedings of the 6th international conference on Advances in web based learning
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To provide an adaptive guidance to the student through learning object repositories, a system needs to have knowledge about the learner as well as material. This paper discusses identification of metadata that describes the pedagogical aspects of a document. Learning goals and prerequisites, if stored as part of metadata, can be utilised for intelligent recommendations. Manual annotation is a time consuming and expensive process. Correct instantiation of learning object metadata requires combined educational and technical skills. This paper proposes natural language processing-based automatic concept extraction and outlines rule-based approach for separation of prerequisite concepts and learning outcomes covered in learning document. The importance of automatic extraction of prerequisite terms is strengthened after evaluation of this work, since results show that concepts missed by authors are suggested by the system. To increase precision of retrieval, subject domain ontology is used.