Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach

Guandong Xu, Yu Zong, Peter Dolog, Yanchun Zhang

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

16 Citationer (Scopus)

Resumé

Web clustering is an approach for aggregating Web objects into various groups according to underlying relationships among them. Finding co-clusters of Web objects is an interesting topic in the context of Web usage mining, which is able to capture the underlying user navigational interest and content preference simultaneously. In this paper we will present an algorithm using bipartite spectral clustering to co-cluster Web users and pages. The usage data of users visiting Web sites is modeled as a bipartite graph and the spectral clustering is then applied to the graph representation of usage data. The proposed approach is evaluated by experiments performed on real datasets, and the impact of using various clustering algorithms is also investigated. Experimental results have demonstrated the employed method can effectively reveal the subset aggregates of Web users and pages which are closely related.
OriginalsprogEngelsk
BogserieLecture Notes in Computer Science
Vol/bind6278
Sider (fra-til)398-407
ISSN0302-9743
DOI
StatusUdgivet - 8 sep. 2010
BegivenhedKnowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff, Storbritannien
Varighed: 8 sep. 201010 sep. 2010
Konferencens nummer: 14th

Konference

KonferenceKnowledge-Based and Intelligent Information and Engineering Systems, KES 2010
Nummer14th
LandStorbritannien
ByCardiff
Periode08/09/201010/09/2010

Fingerprint

Spectral Projection
Clustering Analysis
Clustering algorithms
Websites
Spectral Clustering
Experiments
Web Usage Mining
Graph Representation
Bipartite Graph
Clustering Algorithm
Clustering
Subset
Experimental Results
Experiment

Citer dette

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abstract = "Web clustering is an approach for aggregating Web objects into various groups according to underlying relationships among them. Finding co-clusters of Web objects is an interesting topic in the context of Web usage mining, which is able to capture the underlying user navigational interest and content preference simultaneously. In this paper we will present an algorithm using bipartite spectral clustering to co-cluster Web users and pages. The usage data of users visiting Web sites is modeled as a bipartite graph and the spectral clustering is then applied to the graph representation of usage data. The proposed approach is evaluated by experiments performed on real datasets, and the impact of using various clustering algorithms is also investigated. Experimental results have demonstrated the employed method can effectively reveal the subset aggregates of Web users and pages which are closely related.",
keywords = "co-cluster, spectral clustering, weblogs",
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Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach. / Xu, Guandong; Zong, Yu; Dolog, Peter; Zhang, Yanchun.

I: Lecture Notes in Computer Science, Bind 6278, 08.09.2010, s. 398-407.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

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