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Web Graph Similarity for Anomaly Detection (poster)

Papadimitriou, Panagiotis and Dasdan, Ali and Garcia-Molina, Hector (2008) Web Graph Similarity for Anomaly Detection (poster). In: 17th International World Wide Web Conference (WWW 2008), April 21-25, 2008, Beijing, China.


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Web graphs are approximate snapshots of the web, created by search engines. Their creation is an error-prone procedure 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 notion of graph similarity. Web graph similarity helps measure the amount and significance of changes in consecutive web graphs. These measurements validate how well search engines acquire content from the web. In this paper we study five 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.

Item Type:Conference or Workshop Item (Poster)
Uncontrolled Keywords:anomaly detection; graph similarity; web graph LSH
Subjects:Computer Science > Databases and the Web
Related URLs:Project Homepage
ID Code:861
Deposited By:Import Account
Deposited On:06 May 2008 17:00
Last Modified:29 Apr 2009 21:49

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