Adaptive on-line page importance computation

The computation of page importance in a huge dynamic graph has recently attracted a lot of attention because of the web. Page importance, or page rank is defined as the fixpoint of a matrix equation. Previous algorithms compute it off-line and require the use of a lot of extra CPU as well as disk resources (e.g. to store, maintain and read the link matrix). We introduce a new algorithm OPIC that works on-line, and uses much less resources. In particular, it does not require storing the link matrix. It is on-line in that it continuously refines its estimate of page importance while the web/graph is visited. Thus it can be used to focus crawling to the most interesting pages. We prove the correctness of OPIC. We present Adaptive OPIC that also works on-line but adapts dynamically to changes of the web. A variant of this algorithm is now used by Xyleme. We report on experiments with synthetic data. In particular, we study the convergence and adaptiveness of the algorithms for various sch...

• Type: Conference
• Year: 2003
• Where: WWW
• Authors: Serge Abiteboul, Mihai Preda, Gregory Cobena
• Keywords: Important Pages, Internet Technology, Page Importance, Page Importance Information, WWW 2003