Clique analysis of query log graphs

Abstract

In this paper we propose a method for the analysis of very large graphs obtained from query logs, using query coverage inspection. The goal is to extract semantic relations between queries and their terms. We take a new approach to successfully and efficiently cluster these large graphs by analyzing clique overlap and a priori induced cliques. The clustering quality is evaluated with an extension of the modularity score. Results obtained with real data show that the identified clusters can be used to infer properties of the queries and interesting semantic relations between them and their terms. The quality of the semantic relations is evaluated both using a tf-idf based score and data from the Open Directory Project. The proposed approach is also able to identify and filter out multitopical URLs, a feature that is interesting in itself. © 2009 Springer Berlin Heidelberg.