Journal of Shanghai University(Natural Science Edition) ›› 2014, Vol. 20 ›› Issue (2): 190-198.doi: 10.3969/j.issn.1007-2861.2013.07.003

• Computer Engineering and Science • Previous Articles     Next Articles

Document Clustering Method Based on Association Link Network

HE Xiang, LUO Xiang-feng   

  1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
  • Online:2014-04-26 Published:2014-04-26

Abstract: This paper proposes a document clustering method with adaptive divisions based on association link network. Instead of explicitly offering the number of cluster centers in the traditional document clustering algorithms, categories were acquired auto- matically by detecting the community structure in association link network. Simultane- ously, with the consideration of the high-dimension and sparse word vectors that result in low similarities between the documents, the relationships were mapped between words in association link network to the relationships between the documents. Through the experimental comparisons with other clustering methods, it was found that the proposed clustering method not only obtains a high aggregation accuracy, but also are good at adap- tively discovering the number of cluster centers and distinguishing categories of topics.

Key words: association link network, community detection, document clustering

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