Generation of similarity knowledge flow for intelligent browsing based on semantic link networks
Generation of similarity knowledge flow for intelligent browsing based on semantic link networks
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DOI：
10.1002/cpe.1460
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发表时间：
2009-11
期刊：
影响因子：
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通讯作者：
Xiangfeng Luo;Zheng Xu;Qing Li;Qingliang Hu;Jie Yu;Xinhuai Tang
中科院分区：
文献类型：
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作者：
Xiangfeng Luo;Zheng Xu;Qing Li;Qingliang Hu;Jie Yu;Xinhuai Tang
相似知识流（SKF）是一种科学工作流程，为Web和e-Science环境下的智能浏览提供了有效的技术和理论支持。本文提出了一种基于语义链接网络（SLN）的SKF生成方法。首先，主题由元素模糊认知图表示，然后计算概念/关键词和关系的语义值。第三，计算主题之间的语义相似度，以构建基于 SLN 的概念语义值及其在元素模糊认知图中的关系。这样，关键词层面的相似关系就延伸到了主题层面。借助SLN，根据用户的需求，生成SKF作为主题的浏览路径，引导用户的浏览行为。最后定义SKF的语义值作为评价主题浏览路径的标准。实验结果表明，主题浏览路径很容易被SLN生成的SKF激活。所提出的方法已被证明在Web服务和e-Science应用领域具有很好的前景。版权所有 © 2009 约翰·威利父子有限公司
Similarity Knowledge Flow (SKF) is a kind of scientific workflow, providing an effective technique and theoretical support for intelligent browsing in the Web and e‐Science environment. In this paper, a Semantic Link Networks (SLN) based SKF generation method is proposed. First, the topics are represented by Element Fuzzy Cognitive Maps then the semantic values of concepts/keywords and relations are calculated. Third, semantic similarity degrees between topics are calculated to build SLN‐based semantic values of concepts and their relations in Element Fuzzy Cognitive Maps. In this way, similar relations at the keyword level are extended to the topic level. With the help of SLN and based on user's demand, SKF is generated as the browsing path of topics to guide user browsing behaviors. Finally, the semantic value of SKF is defined as a criterion to evaluate the browsing path of topics. Experimental results show that the browsing path of topics is easy to be activated by SKF which is generated by SLN. The proposed method has been proved to have a very good prospect in the fields of Web services and e‐Science applications. Copyright © 2009 John Wiley & Sons, Ltd.