Implicit link analysis for small web search

Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma, HongJiang Zhang, Chao-Jun Lu
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引用次数: 73

Abstract

Current Web search engines generally impose link analysis-based re-ranking on web-page retrieval. However, the same techniques, when applied directly to small web search such as intranet and site search, cannot achieve the same performance because their link structures are different from the global Web. In this paper, we propose an approach to constructing implicit links by mining users' access patterns, and then apply a modified PageRank algorithm to re-rank web-pages for small web search. Our experimental results indicate that the proposed method outperforms content-based method by 16%, explicit link-based PageRank by 20% and DirectHit by 14%, respectively.
小型网页搜索的隐式链接分析
当前的网络搜索引擎通常在网页检索中强加基于链接分析的重新排序。然而,同样的技术,当直接应用于小型web搜索(如内部网和站点搜索)时,由于它们的链接结构与全局web不同,无法达到相同的性能。在本文中,我们提出了一种通过挖掘用户访问模式来构建隐式链接的方法,然后应用改进的PageRank算法对网页进行重新排名,用于小型网页搜索。我们的实验结果表明,所提出的方法分别比基于内容的方法高出16%,基于显式链接的PageRank高出20%,DirectHit高出14%。
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