Pagerank based clustering of hypertext document collections

Clustering hypertext document collection is an important task in Information Retrieval. Most clustering methods are based on document content and do not take into account the hyper-text links. Here we propose a novel PageRank based clustering (PRC) algorithm which uses the hypertext structure. The PRC algorithm produces graph partitioning with high modularity and coverage. The comparison of the PRC algorithm with two content based clustering algorithms shows that there is a good match between PRC clustering and content based clustering. Categories and Subject Descriptors H.3 [Information Search and Retrieval]: Miscellaneous General Terms Algorithms, Experiments Keywords PageRank based Clustering, Directed Graphs

• Type: Journal
• Year: 2008
• Where: SIGIR
• Authors: Konstantin Avrachenkov, Vladimir Dobrynin, Danil Nemirovsky, Son Kim Pham, Elena Smirnova
• Keywords: Content Based Clustering, Information Technology, Most Clustering Methods, PRC Algorithm, SIGIR 2008