Website Clustering from Query Graph using Social Network Analysis
Along with informationization advancement thorough and Internet rapid development, there exists millions of websites on the Internet. Search engines become a mediator to connect web users and websites. The query logs in which recorded daily contains a wealth of knowledge about the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences, and the behavior of the users, as well as their implicit feedback to search-engine results. By constructing a novel query graph, considering for the classification of queries, which is utilized to build multi-dimensional vector, we adopt social network analysis method to detect communities in the graph to implement website clustering. Website clustering can contribute to spam website, pornographic website and political sensitive website detection. So it can be applied to websites supervision.
component Website Clustering Social Network Analysis Query Logs Websites supervision
Weiduo Wang Bin Wu Zhonghui Zhang
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia,Beijing University of Posts and Telecommunications,Beijing, P.R.China
国际会议
北京
英文
439-442
2010-08-08（万方平台首次上网日期，不代表论文的发表时间）