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基于复杂网络社团划分的Web services聚类 被引量：1

Web services clustering based on detecting community structure in complex network
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摘要 以单词为网络节点,由自然语言描述中单词的同现频率确定单词间的相关度并作为边的权值,构建自然语言描述集合的加权单词网络模型。利用Newman快速算法对加权单词网络模型进行社团划分,得到单词聚类结果;根据单词聚类结果与服务之间的映射关系实现服务聚类。实验结果与手工分类结果的对比表明,平均查准率达74.7%以上。 This paper described an algorithm which created WWN of service descriptions. The nodes was words, and WWN got the edge-weight through the word＇s co-appearance. Newman fast algorithm could detect community structure in WWN and return the clusters of words. Using the relationship between words and services, achieved service-clustering. At last, an experiment on a collection of 1 007 Web services shows the high precision of 74.7%
作者 欧有远 张海粟 孟晖 李德毅
机构地区 解放军理工大学指挥自动化学院 通信指挥学院 中国电子系统工程研究所
出处 《计算机应用研究》 CSCD 北大核心 2009年第6期2299-2302,共4页 Application Research of Computers
基金 国家“973”重点基础研究资助项目(2007CB310800) 国家自然科学基金资助项目(60675032)
关键词 WEB服务 聚类 复杂网络 社团划分 文本聚类 Web services clustering complex networks community structure detecting documents clustering
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献15

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同被引文献9

  • 1况夯,罗军.基于遗传FCM算法的文本聚类[J].计算机应用,2009,29(2):558-560. 被引量：5
  • 2彭京,杨冬青,唐世渭,付艳,蒋汉奎.一种基于语义内积空间模型的文本聚类算法[J].计算机学报,2007,30(8):1354-1363. 被引量：44
  • 3PangningTan,SteinbachM,KumarV数据挖掘导论[M].北京:人民邮电出版社,2006:305-347.
  • 4Luo Congnan,Li Yanjun,Soon M Chung.Text document clustering based on neighbors [J]. Data & Knowledge Engineering, 2009,68(11):1271-1288.
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  • 6Chen D B,Fu Y, Shang M S.A fast and efficient heuristic algorithm for detecting community structures in complex networks [J].Physica A,2009,388:2741-2749.
  • 7Wan Xiaojun.A novel document similarity measure based on earth mover's distance[J].Information Science,2007,177:3718-3730.
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引证文献1

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计算机应用研究
2009年 第6期

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