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Query Clustering for Boosting Web Page Ranking

机译:查询集群以提高网页排名

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摘要

Over the past few years, there has been a great deal of research on the use of content and links of Web pages to improve the quality of Web page rankings returned by search engines. However, few formal approaches have considered the use of search engine logs to improve the rankings. In this paper we propose a ranking algorithm that uses the logs of search engines to boost their retrieval quality. The relevance of Web pages is estimated using the historical preferences of users that appear in the logs. The algorithm is based on a clustering process in which groups of semantically similar queries are identified. The method proposed is simple, has low computational cost, and we show with experiments that achieves good results.
机译:在过去的几年中,已经进行了大量有关使用网页内容和链接以提高搜索引擎返回的网页排名质量的研究。但是,很少有正式的方法考虑过使用搜索引擎日志来提高排名。在本文中,我们提出了一种排序算法,该算法使用搜索引擎的日志来提高其搜索质量。网页的相关性是使用出现在日志中的用户的历史偏好来估计的。该算法基于聚类过程,其中识别出语义相似的查询组。所提出的方法简单,计算成本低,并通过实验证明取得了良好的效果。

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