A Semantic Enabled Intelligent Search System for Educational Information Resources

被引：0

作者：

Huang Chang-qin ^{[1
]}

Duan Ru-lin ^{[1
]}

Zhu Zhi-ting ^{[2
]}

Yan Yong-jian ^{[1
]}

Bai Hui ^{[3
]}

机构：

[1] S China Normal Univ, Sch Educ Informat Technol, Guangzhou 510631, Guangdong, Peoples R China

[2] E China Normal Univ, Dept Educ Informat Technol, Shanghai 200062, Peoples R China

[3] South China Univ Technol, Res Inst Comp Syst, Guangzhou 510006, Peoples R China

来源：

2009 IEEE INTERNATIONAL SYMPOSIUM ON IT IN MEDICINE & EDUCATION, VOLS 1 AND 2, PROCEEDINGS | 2009年

基金：

中国博士后科学基金;

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：539 / +

页数：2

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