Clustering of document collection – A weighting approach

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Clustering algorithms are used to assess the interaction among documents by organizing documents into clusters such that document within a cluster are more similar to each other than are documents belonging to different clusters. Document clustering has been traditionally investigated as a means of improving the performance of search engines by pre-clustering the entire corpus, and a post-retrieval document browsing technique as well. It has long been studied as a post-retrieval document visualization technique. The purpose of present paper to show that assignment weight to documents improves clustering solution.

论文关键词:Text mining,Weighted partitional clustering,Adjusted cosine similarity measure,Validity index,Differential evolution

论文评审过程:Available online 27 November 2008.

论文官网地址:https://doi.org/10.1016/j.eswa.2008.11.017