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本体学习研究综述
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Supported by the National Natural Science Foundation of China under Grant Nos.60496325,60573092(国家自然科学基金)

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    摘要:

    近年来,本体学习技术逐渐成为计算机科学领域的一个研究热点.根据数据源的结构化程度(结构化、半结构化、非结构化)以及本体学习对象的层次(概念、关系、公理),将本体学习问题划分为9类子问题.分别阐述了这9类问题的基本特征、常用的方法和最新的研究进展,并在此分析框架下进一步介绍和比较了现有的本体学习工具.最后,讨论了存在的问题,指出了未来的研究方向.

    Abstract:

    Recently, ontology learning is emerging as a new hotspot of research in computer science. In this paper the issue of ontology learning is divided into nine sub-issues according to the structured degree (structured, semi-structured, non-structured) of source data and learning objects (concept, relation, axiom) of ontology. The characteristics, major approaches and the latest research progress of the nine sub-issues are summarized. Based on the analysis framework proposed in the paper, existing ontology learning tools are introduced and compared. The problems of current research are discussed, and finally the future directions are pointed out.

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杜小勇,李曼,王珊.本体学习研究综述.软件学报,2006,17(9):1837-1847

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  • 收稿日期:2005-11-22
  • 最后修改日期:2006-02-23
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