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Adaptive on-line page importance computation

Adaptive on-line page importance computation Adaptive On-Line Page Importance Computation Serge Abiteboul INRIA Domaine de Voluceau 78150 Rocquencourt, France Mihai Preda Xyleme S.A. 6 rue Emile Verhaeren 92210 Saint-Cloud, France Gregory Cobena INRIA Domaine de Voluceau 78150 Rocquencourt, France [email protected] ABSTRACT [email protected] [email protected] often1 and when crawling for new pages, important pages have to be fetched rst [9]. Following some ideas of [18], Page and Brin proposed a notion of page importance based on the link structure of the web [5]. This was then used by Google with a remarkable success. Intuitively, a page is important if there are many important pages pointing to it. This leads to a xpoint computation by repeatedly multiplying the matrix of links between pages with the vector of the current estimate of page importance until the estimate is stable, i.e., until a xpoint is reached. The main issue in this context is the size of the web, billions of pages [4, 23]. Techniques have been developed to compute page importance ef ciently, e.g., [16]. The web is crawled and the link matrix computed and stored. A version of the matrix is then frozen and one separate process computes off-line page importance, which may take hours or days http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Adaptive on-line page importance computation

Abiteboul, Serge; Preda, Mihai; Cobena, Gregory
Association for Computing Machinery — May 20, 2003
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Datasource
Association for Computing Machinery
Copyright
Copyright © 2003 by ACM Inc.
ISBN
1-58113-680-3
doi
10.1145/775152.775192
Publisher site
See Article on Publisher Site

Abstract

Adaptive On-Line Page Importance Computation Serge Abiteboul INRIA Domaine de Voluceau 78150 Rocquencourt, France Mihai Preda Xyleme S.A. 6 rue Emile Verhaeren 92210 Saint-Cloud, France Gregory Cobena INRIA Domaine de Voluceau 78150 Rocquencourt, France [email protected] ABSTRACT [email protected] [email protected] often1 and when crawling for new pages, important pages have to be fetched rst [9]. Following some ideas of [18], Page and Brin proposed a notion of page importance based on the link structure of the web [5]. This was then used by Google with a remarkable success. Intuitively, a page is important if there are many important pages pointing to it. This leads to a xpoint computation by repeatedly multiplying the matrix of links between pages with the vector of the current estimate of page importance until the estimate is stable, i.e., until a xpoint is reached. The main issue in this context is the size of the web, billions of pages [4, 23]. Techniques have been developed to compute page importance ef ciently, e.g., [16]. The web is crawled and the link matrix computed and stored. A version of the matrix is then frozen and one separate process computes off-line page importance, which may take hours or days

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