%0 Journal Article
%T Web search result clustering based on K-center and information gain<br>基于 K-center和信息增益的 Web搜索结果聚类方法 *
%A DING Zhen-guo
%A MENG Xing
%A <br>丁振国
%A 孟星
%J 计算机应用研究
%D 2008
%I 
%X Based on K-center and informationgain, this paper represented aversion of modified FPF algorithman dclusterla-beling algorithm on Web search clustering, made the result better understood. At last, presented a simple and intuitionistic criterion NMI for estimating cluster quality. The proposed solution was evaluated in search results returned from actual Web search engine and compared with other methods, like Lingo, K-means. The result proves that the algorithm can balance better clustering time and quality, and meets the requirements of Web searching clustering.
%K Web document
%K clustering
%K cluster labeling
%K K-center
%K information gain<br>Web文档
%K 聚类
%K 聚类标志
%K K-center
%K 信息增益
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=7472D6B186ED144845DAEA8703CAB924&yid=67289AFF6305E306&vid=C5154311167311FE&iid=F3090AE9B60B7ED1&sid=3B4BF8D06704D13B&eid=67B3357EDFB0796A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=1&reference_num=10