Document clustering based on web search hit counts
by Masaya Kaneko; Shusuke Okamoto; Masaki Kohana; You Inayoshi
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 8, No. 1, 2013

Abstract: This paper describes a web mining method for clustering research documents automatically. Web hit counts of AND-search for two words are used to form a document feature vector. Target documents are clustered using the k-means clustering method twice, in which cosine similarity is used to calculate the distance measure.

Online publication date: Sat, 28-Jun-2014

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