Web Graph Similarity for Anomaly Detection (Poster)
Web graphs are approximate snapshots of the web, created by search engines. Their creation is an error-prone proce-dure that relies on the availability of Internet nodes and the faultless operation of multiple software and hardware units. Checking the validity of a web graph requires a no-tion of graph similarity. Web graph similarity helps measure the amount and signi cance of changes in consecutive web graphs. These measurements validate how well search en-gines acquire content from the web. In this paper we study vfive similarity schemes: three of them adapted from existing graph similarity measures and two adapted from well-known document and vector similarity methods. We compare and evaluate all five schemes using a sequence of web graphs for Yahoo! And study if the schemes can identify anomalies that may occur due to hardware or other problems.
anomaly detection graph similarity web graph LSH
Panagiotis Papadimitriou Ali Dasdan Hector Garcia-Molina
Stanford University Stanford, CA 94305, USA Yahoo! Inc.Sunnyvale, CA 94089, USA
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）