Abstract: Clustering display of search results has been proved an efficient way to organize the Web resources.However，for a given query，clustering results reached by any user are totally identical.A novel search method based on clustering is proposed，which is a modified version of k-means algorithm.The results generated from usual search engine go through a clustering stage based on user interests to create user-specific clusters.Experiments show that it can offer user-specific information needs，improve clustering effectiveness and searching efficiency.

摘要： 实践证明聚类技术是改进搜索结果显示方式的一种有效手段。然而，目前的聚类方法没有考虑到用户兴趣，对于相同的查询，返回给所有用户同样的聚类结果。由此提出一种个性化聚类检索方法。该方法改进了k-means算法，利用该算法对传统搜索引擎返回的结果结合用户兴趣进行聚类，返回针对特定用户的网页簇。实验证明该方法能够提供个性化服务，改善了聚类的效果，提高了用户的检索效率。