Apply Formal Concept Analysis to Teaching Material Extraction
Shao-Chun Li, Ko-Kang Chu, Department of Information Communication, MingDao University, Taiwan ; Maiga Chang, School of Computing & Information Systems, Athabasca University, Canada
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Vancouver, Canada ISBN 978-1-880094-76-1 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
Text summarization system can save the time for user when reading large number of documents. The summary of text summarization system usually composed of meaningful sentence which represent content of text. A summary should cover whole document content and help user understand document quickly. The relations between keyword usually come from their co-occurrences in document. This study using hierarchical clustering method cluster sentences and apply concept formal analysis to find out the implications between keywords. The position of sentence appears in document also influence the importance of sentence. Finally the system selects sentences which represent document according to the weight of keywords, implications between keywords and position in document. In this research, we present an automatic text summarization system which can extract important keywords from document automatic and offer a short summary represent document.
Li, S.C., Chu, K.K. & Chang, M. (2009). Apply Formal Concept Analysis to Teaching Material Extraction. In T. Bastiaens, J. Dron & C. Xin (Eds.), Proceedings of E-Learn 2009--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 481-487). Vancouver, Canada: Association for the Advancement of Computing in Education (AACE).
© 2009 Association for the Advancement of Computing in Education (AACE)
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