NDLI: A semantic enabled intelligent search system for educational information resources

Content Provider	IEEE Xplore Digital Library
Author	Huang Chang-qin Duan Ru-lin Zhu Zhi-ting Yan Yong-jian Bai Hui
Copyright Year	2009
Description	Author affiliation: Department of Education Information Technology, East China Normal University, Shanghai, 200062, China (Zhu Zhi-ting) \|\| Research Institute of Computer Systems, South China University of Technology, Guangzhou, 510006, China (Bai Hui) \|\| School of Educational Information Technology, South China Normal University, Guangzhou, 510631, China (Huang Chang-qin; Duan Ru-lin; Yan Yong-jian)
Abstract	Aiming at the special requirements oriented to the education field, this paper proposes an intelligent search system based on semantic web. Under the guidance of the users' needs and the proposed Education Information Intelligent Search (EIIS) framework, the EIISReasoning mechanism and its relevant rule sets are constructed to automatically reason the search concepts in order to self-adapt semantics to more levels, where the semantic factor SR and the response time factor TR are both introduced to detail field application requirements. After this, the EIISRanking algorithm applies two levels ranking by the weight factor of semantic similarity, and the same relevance is differentiated in terms of education field needs. The case test shows that the semantic based intelligent search system takes on a better precision rate, and the ranking algorithm can improve execution performance.
Starting Page	539
Ending Page	544
File Size	224800
Page Count	6
File Format	PDF
ISBN	9781424439287
DOI	10.1109/ITIME.2009.5236361
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Semantic Web Information resources Search engines Ontologies Computer science education Intelligent systems Information technology Machine intelligence Delay Intelligent agent
Content Type	Text
Resource Type	Article

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