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2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW) (2006)
Atlanta, Georgia
Apr. 3, 2006 to Apr. 7, 2006
ISBN: 0-7695-2571-7
pp: 40
Sophoin Khy , University of Tsukuba, Japan
Yoshiharu Ishikawa , University of Tsukuba, Japan
Hiroyuki Kitagawa , University of Tsukuba, Japan
ABSTRACT
Document clustering has been used as a core technique in managing vast amount of data and providing needed information. In on-line environments, generally new information gains more interests than old one. Traditional clustering focuses on grouping similar documents into clusters by treating each document with equal weight. We proposed a novelty-based incremental clustering method for on-line documents that has biases on recent documents. In the clustering method, the notion of ?novelty? is incorporated into a similarity function and a clustering method, a variant of the K-means method, is proposed. We examine the efficiency and behaviors of the method by experiments.
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CITATION
Sophoin Khy, Yoshiharu Ishikawa, Hiroyuki Kitagawa, "Novelty-based Incremental Document Clustering for On-line Documents", 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW), vol. 00, no. , pp. 40, 2006, doi:10.1109/ICDEW.2006.100
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