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Selecting Web Search Results of Diverse Contents with Search Engine Suggests and a Topic Model

机译:使用搜索引擎建议和主题模型选择各种内容的Web搜索结果

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In this paper, we address the issue of how to overview the knowledge ofa given query keyword. We especially focus on concerns of those whosearch for Web pages with a given query keyword, and study how toefficiently overview the whole list of Web search information needs of agiven query keyword. First, we collect Web search information needs ofa given query keyword through search engine suggests. Although wecollect up to around 1,000 suggests given a query keyword, some of themare redundant in that they originate from almost the same Web searchinformation needs. In order to aggregate such redundant search enginesuggests, we take an approach of clustering search engine suggests basedon a topic model. Evaluation result shows that the proposed clusteringapproach proves to be quite useful for efficiently overviewing Websearch information needs of a given query keyword. We also develop aninterface system for overviewing those aggregated search engine suggestsof a given query keyword as well as links to top ranked Web pages thatare closely related to those aggregated search engine suggests. Finally, we show the effectiveness of the interface in terms of theaggregation of Web search results.
机译:在本文中,我们解决了如何概述给定查询关键字的知识的问题。我们特别关注那些使用给定查询关键字搜索网页的人们的关注,并研究如何有效地概述给定查询关键字的Web搜索信息需求的整个列表。首先,我们通过搜索引擎建议收集给定查询关键字的Web搜索信息需求。尽管我们收集多达1,000条给定查询关键字的建议,但其中一些是多余的,因为它们源自几乎相同的Web搜索信息需求。为了聚合这样的冗余搜索引擎建议,我们采用基于主题模型对搜索引擎建议进行聚类的方法。评估结果表明,所提出的聚类方法被证明对于有效地概述给定查询关键字的Websearch信息需求非常有用。我们还开发了一个界面系统,用于概述给定查询关键字的聚合搜索引擎建议以及与那些聚合搜索引擎建议密切相关的排名最高的网页的链接。最后,我们从Web搜索结果的聚合方面展示了该界面的有效性。

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