基于用户行为聚类的搜索

因特网的飞速发展,网络资源呈爆炸式的增长。信息检索是人们上网的主要目的之一。目前的信息检索领域有许多检索方法与检索工具,为用户检索信息提供了许多途径。但如何利用搜索引擎实现更快更精确的搜索已经成为这一领域的研究热点。在研究现有的几种搜索引擎的基础上,提出了一种基于用户行为聚类的搜索引擎。通过分析不同的用户行为将搜索用户聚类成不同的用户组,为每组用户返回其喜欢的结果,优化查询结果。

A Search Engine Based on User Behavior Clustering

With the rapid growth of Internet, the network resource is increasing explosively. Information retrieval is one of main purposes as we browse Internet. At present, there are many retrieval methods and retrieval tools in information retrieval field, users could use all of these avenues to retrieve information. But how to increase the rapidity and precision has become the hotpot in this field. In this paper, a optimizing search based on user behavior analysis clustering is presented. Cluster the users into different group by analyse different user behavior,optimizing the query results.