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Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search
| Title: | Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search |
| Authors: | Okubo, Yoshiaki1 Browse this author →KAKEN DB | | Haraguchi, Makoto Browse this author →KAKEN DB | | Shi, Bin Browse this author |
| Authors(alt): | 大久保, 好章1 |
| Issue Date: | 8-Oct-2005 |
| Publisher: | Springer |
| Journal Title: | Discovery Science |
| Volume: | 3735 |
| Start Page: | 346 |
| End Page: | 353 |
| Publisher DOI: | 10.1007/11563983_30 |
| Abstract: | In this paper, we discuss a method of finding useful clusters of web pages which are significant in the sense that their contents are similar or closely related to ones of higher-ranked pages. Since we are usually careless of pages with lower ranks, they are unconditionally discarded even if their contents are similar to some pages with high ranks. We try to extract such hidden pages together with significant higher-ranked pages as a cluster.
In order to obtain such clusters, we first extract semantic correlations among terms by applying Singular Value Decomposition(SVD) to the term-document matrix generated from a corpus w.r.t. a specific topic. Based on the correlations, we can evaluate potential similarities among web pages from which we try to obtain clusters. The set of web pages is represented as a weighted graph G based on the similarities and their ranks. Our clusters can be found as pseudo-cliques in G. We present an algorithm for finding Top-N weighted pseudo-cliques. Our experimental result shows that quite valuable clusters can be actually extracted according to our method. |
| Rights: | The original publication is available at www.springerlink.com |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/5773 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 大久保 好章
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