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Linguistic Valued Association Rules

Linguistic Valued Association Rules
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摘要 Association rules discovering and prediction with data mining method are two topics in the field of information processing. In this paper, the records in database are divided into many linguistic values expressed with normal fuzzy numbers by fuzzy c-means algorithm, and a series of linguistic valued association rules are generated. Then the records in database are mapped onto the linguistic values according to largest subject principle, and the support and confidence definitions of linguistic valued association rules are also provided. The discovering and prediction methods of the linguistic valued association rules are discussed through a weather example last. Association rules discovering and prediction with data mining method are two topics in the field of information processing. In this paper, the records in database are divided into many linguistic values expressed with normal fuzzy numbers by fuzzy c-means algorithm, and a series of linguistic valued association rules are generated. Then the records in database are mapped onto the linguistic values according to largest subject principle, and the support and confidence definitions of linguistic valued association rules are also provided. The discovering and prediction methods of the linguistic valued association rules are discussed through a weather example last.
出处 《Systems Science and Systems Engineering》 CSCD 2002年第4期409-413,共5页 系统科学与系统工程学报(英文版)
基金 The projectis supported by N ational N atural Science Foundation of China(No.699310 4 0 )
关键词 data mining fuzzy c-means algorithm linguistic valued association rules data mining fuzzy c-means algorithm linguistic valued association rules
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参考文献3

  • 1[1]Agrawal R,Imieliski T,Swami A.Mining association rules between sets of items in large databases.Proceedings of ACM SIGMOD Conference on Management of Data Washington,DC,1993,207~216.
  • 2[2]Agrawal R,Srikant R.Fast algorithms for mining association rules.Proceedings of the 1994 International Conference on Very Large Databases.Santiago,Chile,1994,487~499.
  • 3[3]Hathaway R J,Davenport J W,Bezdek J C.Relational dual of the c-means clustering algorithms.Pattern Recognition,1989,22(2):205~212.

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