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Dynamic Clustering of Web Search Results

机译:Web搜索结果的动态聚类

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摘要

A problem in Web searches is how to help users quickly find useful links from a long list of returned URLs. Document clustering provides an approach to organize retrieval results by clustering documents into meaningful groups. Because a word in a document is naturally correlated with neighboring words, document clustering often uses phrases rather than individual words in determining clusters. We have designed a system to cluster Web search results based on phrases that contain one or more search keywords. We show that, rather than clustering based on whole documents, clustering based on phrases containing search keywords often gives more accurate and informative clusters. Algorithms and experimental results are discussed.
机译:Web搜索中的问题是如何帮助用户从返回的URL的长期列表中快速查找有用的链接。文档群集提供了一种方法来组织通过将文档组织成有意义的群体来组织检索结果。因为文档中的单词与邻居单词自然相关,所以文档群集通常使用短语而不是确定群集中的单个单词。我们设计了一个基于包含一个或多个搜索关键字的短语的网络搜索结果。我们展示了,而不是基于整个文档的聚类,基于包含搜索关键字的短语的群集通常提供更准确和信息丰富的群集。讨论了算法和实验结果。

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