Co-clustering for weblogs in semantic space

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Zong, Yu, Xu, Guandong, Dolog, Peter, Zhang, Yanchun and Liu, Renjin (2010) Co-clustering for weblogs in semantic space. In: Web information systems engineering, WISE 2010 : 11th International Conference, Hong Kong, China, December 12-14, 2010 : proceedings. Chen, Lei, Triantafillou, Peter and Suel, Torsten, eds. Lecture notes in computer science (6488). Springer, Berlin, pp. 120-127.


Web clustering is an approach for aggregating web objects into various groups according to underlying relationships among them. Finding co-clusters of web objects in semantic space 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 a novel web co-clustering algorithm named Co-Clustering in Semantic space (COCS) to simultaneously partition web users and pages via a latent semantic analysis approach. In COCS, we first, train the latent semantic space of weblog data by using Probabilistic Latent Semantic Analysis (PLSA) model, and then, project all weblog data objects into this semantic space with probability distribution to capture the relationship among web pages and web users, at last, propose a clustering algorithm to generate the co-cluster corresponding to each semantic factor in the latent semantic space via probability inference. The proposed approach is evaluated by experiments performed on real datasets in terms of precision and recall metrics. Experimental results have demonstrated the proposed method can effectively reveal the co-aggregates of web users and pages which are closely related.

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Item type Book Section
DOI 10.1007/978-3-642-17616-6_12
Official URL
ISBN 9783642176159 (print), 9783642176166 (online)
Subjects Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > FOR Classification > 0806 Information Systems
Historical > Faculty/School/Research Centre/Department > School of Engineering and Science
Keywords ResPubID21730, projecting data objects into semantic space
Citations in Scopus 2 - View on Scopus
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