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2006
IEEE

Novelty-based Incremental Document Clustering for On-line Documents

11 years 5 months ago
Novelty-based Incremental Document Clustering for On-line Documents
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.
Sophoin Khy, Yoshiharu Ishikawa, Hiroyuki Kitagawa
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICDE
Authors Sophoin Khy, Yoshiharu Ishikawa, Hiroyuki Kitagawa
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