User-Assisted Similarity Estimation for Searching Related Web Pages

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Description

To utilize the similarity information hidden in the Web graph, we investigate the problem of adaptively retrieving related Web pages. Given a definition of similarities between pages, it is intuitive to estimate that any similarity will propagate from page to page, inducing an implicit topical relatedness between pages. In this paper, we extract connected subgraphs from the whole graph that consists of all pairs of similar pages, and then sort the candidates of related pages by anovel rank measure which is based on the combination distances of a flexible hierarchical clustering. Moreover, due to the subjectivity of similarity values, we adaptively supply the ordering list of related pages according to an adjustable parameter. The experiments with three similarity measures demonstrate that using in-link information is favorable while using a combination measure of in-links and out-links lowers the precision of identifying similar pages.

Journal

  • 全国大会講演論文集

    全国大会講演論文集 第70回 (「情報爆発」時代に向けた新しいIT技術基盤), 67-68, 2008-03-13

    情報処理学会

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