对检索结果进行聚类能够方便用户从搜索结果中快速地找到自己需要的信息,当前已有各种聚类方法和系统被广泛使用,但是,现有大部分方法由于聚类标签的可读性和描述性较差,难以达到预期效果。该文提出了一种新的思路,注重于如何在聚类之前就产生好的标签,在生成了标签的基础上,再进行检索结果聚类。对于搜索引擎返回的结果,我们先统一建立一棵后缀树,然后计算后缀树中各个短语的得分,选取得分最高的若干短语作为候选标签。得到标签后,将搜索引擎返回的各个结果项分配到它所包含的标签对应的分类中,形成最后的聚类。实验表明,我们的方法是比较有效的。

Organizing web search results into clusters is helpful for users to browse through search results. Many clustering methods have been widely used for this purpose, but most of them do not work well because the generated cluster labels are not readable and informative enough for users to identify the right cluster quickly. In this paper, we focus on how to generate more readable cluster labels and propose a novel method to address this problem. Based on the ranked list of snippets returned by a web search engine for a given query, we first construct a suffix tree for these snippets. Then we calculate scores for all the phrases in the tree by leveraging their statistic and syntactic information. Finally, we rank the phrases in descending order of their scores, and then select the top k phrases as the final cluster labels. Having the labels, we can form clusters by assigning each snippet to the relevant label. Experimental results show that our method works well for clustering web search results.