Journal of Guangdong University of Technology ›› 2014, Vol. 31 ›› Issue (3): 32-38.doi: 10.3969/j.issn.1007-7162.2014.03.006

• Comprehensive Studies • Previous Articles     Next Articles

Some Challenges in Clustering Analysis

Jiang Sheng-yi1, Wang Lian-xi2   

  1. 1.Cisco School of Informatics；2. Library, Guangdong University of Foreign Studies, Guangzhou 510420, China
  • Received:2014-07-10 Online:2014-09-30 Published:2014-09-30

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Abstract: The aim of clustering is to help people find and recognize the unknown world, so as to accumulate knowledge for us in real life. Clustering analysis is an important part for the majority of researchers in unsupervised leaning, and is usually used as an analysis tool to explore the unknown data and its regularity for many cross subjects. It analyzed the procedure of clustering, and briefly surveyed the related achievements. Moreover, the problems of clustering algorithms in processing various data types, high dimensional data, unbalanced data were concluded, and the expansibility and the selection of evaluation index for algorithms were also discussed in detail. At last, some directions for future research were proposed. The above work can give valuable reference to further studies of clustering and data mining.

Key words: clustering analysis, unsupervised learning, data mining

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