Modeling and exploiting tag relevance for Web service mining
Modeling and exploiting tag relevance for Web service mining
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DOI：
10.1007/s10115-013-0703-1
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发表时间：
2013-11
影响因子：
2.7
通讯作者：
Liang Chen;Jian Wu;Zibin Zheng;Michael R. Lyu;Zhaohui Wu
中科院分区：
文献类型：
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作者：
Liang Chen;Jian Wu;Zibin Zheng;Michael R. Lyu;Zhaohui Wu
Web 服务标签，即用户注释的用于描述 Web 服务的功能或其他方面的术语，被视为 Web 服务挖掘的集体用户知识。由于用户标记本质上是不受控制的、模糊的和过度个性化的，因此一个关键且基本的问题是如何衡量用户贡献的标记与带注释的 Web 服务的功能的相关性。在本文中，我们提出了一种混合机制，通过使用Web服务描述语言文档和服务标签网络信息，分别采用语义计算和超链接引发的主题搜索模型来计算标签的相关性分数。进一步，我们将标签相关性度量机制引入到Web服务挖掘的三个应用中：（1）Web服务聚类； (2) Web服务标签推荐； (3)基于标签的Web服务检索。为了评估标签相关性度量的准确性及其对Web服务挖掘的影响，在基于15968个真实Web服务构建的Web服务搜索引擎Titan上进行了实验。综合实验证明了所提出的标签相关性度量机制的有效性以及对标签数据在Web服务挖掘中的使用的积极促进。
Web service tags, i.e., terms annotated by users to describe the functionality or other aspects of Web services, are being treated as collective user knowledge for Web service mining. Since user tagging is inherently uncontrolled, ambiguous, and overly personalized, a critical and fundamental problem is how to measure the relevance of a user-contributed tag with respect to the functionality of the annotated Web service. In this paper, we propose a hybrid mechanism by using Web Service Description Language documents and service-tag network information to compute the relevance scores of tags by employing semantic computation and Hyperlink-Induced Topic Search model, respectively. Further, we introduce tag relevance measurement mechanism into three applications of Web service mining: (1) Web service clustering; (2) Web service tag recommendation; and (3) tag-based Web service retrieval. To evaluate the accuracy of tag relevance measurement and its impact to Web service mining, experiments are implemented based onTitanwhich is a Web service search engine constructed based on 15,968 real Web services. Comprehensive experiments demonstrate the effectiveness of the proposed tag relevance measurement mechanism and its active promotion to the usage of tagging data in Web service mining.