一种基于后缀树的Web搜索结果聚类方法

A Clustering Method for Web Search Results Based on Suffix Tree

为同时满足Web搜索结果聚类的关联性、快速性以及类别描述的可浏览性等需求，本文提出了一种适合中文Web信息搜索结果的后缀树聚类算法，其中后缀树的构建以中文汉字为基本单位，一种有效的策略解决了基于二进制方法合并短语类后的类别描述问题，利用短语类语义层面的相似性合并同义短语类，有效地改善了聚类结果的质量。测试结果表明：与传统的文档聚类算法相比，基于后缀树的算法在Web文档聚类的精度和效率方面具有较强的优越性。

In order to satisfy the key requirements for Web document clustering, including relevance, speed, browseable summaries and so on, a method called Suffix Tree Clustering （STC） algorithm is proposed for Web search results clustering in Chinese context. The suffix tree in the paper is built in terms of Chinese words. An effective strategy is introduced into solving the problem of cluster description for cluster merging based on the binary similarity measure, and also similar phrase clusters are merged based on the semantic similarity calculation to improve the quality of clusters. Experiments show that the proposed STC algorithm has a better performance in both precision and speed than traditional document clustering algorithms.