JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (3): 1-6.doi: 10.6040/j.issn.1672-3961.3.2014.127

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Twice clustering method based on variable granularity

ZHU Hong1,2, DING Shifei2   

  1. 1. School of Medical Information, Xuzhou Medical College, Xuzhou 221005, Jiangsu, China;
    2. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China
  • Received:2014-10-08 Revised:2015-05-11 Online:2015-06-20 Published:2014-10-08

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Abstract: In order to make up the deficiency of single clustering algorithm, a new twice clustering method based on the variable granularity and clustering network (VGTC) was presented, which combined granularity computing with clustering algorithms together. The aim of the first clustering was to find local data structure through searching an appropriate clustering layer. On this basis, the secondary clustering could complete clustering operation for domain. The creativity of VGTC was that the granularity of clustering could be adjusted by changing clustering algorithm parameters, and the advantages of two clustering algorithms could be combined together through granularity computing. The twice clustering adaptive method of variable granulation based on k-means and hierarchical clustering algorithms(KHVGTC was an example of VGTC) verified the accuracy and efficiency of VGTC algorithm by theory analysis and experimental results.

Key words: clustering network, twice clustering, VGTC, granularity computing, KHVGTC, clustering layer

CLC Number: 

  • TP181
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