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A Phrase-Based Method for Hierarchical Clustering of Web Snippets

机译:Web片段的分层聚类的基于短语的方法

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Document clustering has been applied in web information retrieval, which facilitates users' quick browsing by organizing retrieved results into different groups. Meanwhile, a tree-like hierarchical structure is well-suited for organizing the retrieved results in favor of web users. In this regard, we introduce a new method for hierarchical clustering of web snippets by exploiting a phrase-based document index. In our method, a hierarchy of web snippets is built based on phrases instead of all snippets, and the snippets are then assigned to the corresponding clusters consisting of phrases. We show that, as opposed to the traditional hierarchical clustering, our method not only presents meaningful cluster labels but also improves clustering performance.
机译:文档聚类已应用于Web信息检索中,通过将检索到的结果组织到不同的组中来促进用户的快速浏览。同时,树状的层次结构非常适合组织检索结果,以使Web用户受益。在这方面,我们通过利用基于短语的文档索引引入了一种用于Web片段的层次聚类的新方法。在我们的方法中,基于片段而不是所有片段构建Web片段的层次结构,然后将片段分配给由短语组成的相应群集。我们证明,与传统的分层聚类相反,我们的方法不仅提供了有意义的聚类标签,而且还提高了聚类性能。

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