计算机应用 ›› 2012, Vol. 32 ›› Issue (01): 191-195.DOI: 10.3724/SP.J.1087.2012.00191

• 数据库技术 • 上一篇    下一篇

基于领域本体的电子学习资源库模型

张沪寅,张铭洋,李鑫   

  1. 武汉大学 计算机学院,武汉 430072
  • 收稿日期:2011-06-17 修回日期:2011-08-10 发布日期:2012-02-06 出版日期:2012-01-01
  • 通讯作者: 张沪寅
  • 作者简介:张沪寅(1962-),男,江苏苏州人,教授,博士,主要研究方向:E-learning、计算机网络、新一代网络体系结构、应用层组播;张铭洋(1986-),男,河南信阳人,硕士研究生,主要研究方向:计算机网络、多媒体;李鑫(1989-),男,安徽阜阳人,博士研究生,主要研究方向:E-learning、分布式存储、计算机网络。
  • 基金资助:

    中央高校基本科研业务费专项(3105005);武汉市创新人才开发资金资助项目(武人社[2009]97号);武汉市科学技术局科技计划项目(201010621209)

E-learning resource library model based on domain ontology

ZHANG Hu-yin,ZHANG Ming-yang,LI Xin   

  1. School of Computer, Wuhan University, Wuhan Hubei 430072, China
  • Received:2011-06-17 Revised:2011-08-10 Online:2012-02-06 Published:2012-01-01
  • Contact: ZHANG Hu-yin

摘要: 随着电子学习系统快速的发展,电子学习资源呈现爆炸式的增长,如何有效地组织海量电子学习资源成为构建高效电子学习系统的重要因素。针对现有资源库在资源组织方面存在的不足,提出了一个基于领域知识本体的电子学习资源库检索模型,该模型利用领域知识来构建领域知识本体库并通过抽取电子学习资源元数据构建元数据库,通过映射关系完成对电子学习资源的语义组织,并在此基础之上构建一个语义检索模型,以有效地解决现有电子学习资源检索中丢失语义背景的问题,使检索结果在查全率、查准率方面有所提高,更加符合用户的需求。

关键词: 电子学习资源库, 检索, 语义, 领域本体, 元数据

Abstract: With the rapid development of E-learning system, E-learning resources grow explosively. How to effectively organize E-learning resources is a key factor of constructing efficient E-learning system. Concerning the existing resources organization deficiency of E-learning resource library, this paper proposed an E-learning resource retrieval model based on domain ontology. This model built a domain knowledge library by making use of the domain knowledge and constructed E-learning resources metadata database by extracting resources metadata, realized semantic organization of E-learning resources through mapping relations, and constructed a semantic retrieval model on this basis, in order to effectively solve the problem of the loss of semantic background in the E-learning resource retrieving. The model has also enhanced the recall rate and the precision rate on the retrieval results, and it is more in line with the needs of the users.

Key words: E-learning resource library, retrieval, semantic, domain ontology, metadata

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