NDLI: Fuzzy ontology generation model using fuzzy clustering for learning evaluation

Content Provider	IEEE Xplore Digital Library
Author	Qing Yang Wei Chen Bin Wen
Copyright Year	2009
Description	Author affiliation: Department of Computer Science, HuaZhong Normal University, Wuhan 430079, China (Qing Yang; Wei Chen; Bin Wen)
Abstract	For expressing the fuzziness and uncertainty of domain knowledge, realizing the semantic retrieval of fuzzy information, this paper produces an extended fuzzy ontology model and proposes a kind of semantic query expansion technology which can implement semantic information query based on the property values and the relationships of fuzzy concepts. The extended fuzzy ontology provides appropriate support for Learning Evaluation. To access the effect of the proposed model, many experiments have been given for the performance evaluation. The results show that this system can improve retrieval accuracy and promote intelligent semantic query.
Starting Page	682
Ending Page	685
File Size	201338
Page Count	4
File Format	PDF
ISBN	9781424448302
DOI	10.1109/GRC.2009.5255035
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Computer science Fuzzy sets Uncertainty semantic information retrieval fuzzy clustering Ontologies Information retrieval Appropriate technology Data mining Fuzzy reasoning fuzzy ontology
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Fuzzy ontology generation model using fuzzy clustering for learning evaluation