摘要
Internet上专题资源网页汇聚和检索是垂直搜索引擎中的核心问题,HITS算法是早期解决这个问题的经典算法,很多文献对它进行了改进,但无论索引的主题相关率还是引擎的查准率都有提高的余地。提出一种基于锚文本和标题信息过滤并结合网页内容相关度判断的HITS专题检索策略,利用专题训练集判断主题相关度,很好地解决了只依靠查询字符串判断的弊端。实验表明,此策略能很好地提高专题信息汇聚精确度和检索的准确率,并且减少了非相关URL的下载量。
The strategy of topic distillation and retrieval on Internet is the key work in research of vertical search engine. HITS algorithm is a classical method for this problem at an earlier time, and some improvements are made by other researchers afterwards. Nevertheless, no matter the theme relation rate or accuracy grade of engine still have room to be improved. This paper proposed a strategy of topic distillation and retrieval by filtering Web pages based on anchor texts and titles combining relation grade of Web pages. Using the topic training collection to judge relation grade could overcome the shortcomings of depending on inquiring strings. The experiment results prove that this strategy can improve the accuracy of topic distillation and retrieval, and reduce the downloaded information of unrelated URLs.
出处
《计算机应用研究》
CSCD
北大核心
2010年第6期2106-2108,共3页
Application Research of Computers
关键词
HITS算法
锚文本
网页标题
专题相关度
向量模型
专题训练集
HITS algorithm
anchor text
Web page title
relation grade of topic
vector model
topic training collection
