A fuzzy logic based method to acquire user threshold of minimum-support for mining association rules

  • Authors:

  • Shichao Zhang;Jingli Lu;Chengqi Zhang

  • Affiliations:

  • School of Maths and Computing, Guangxi Normal Univiersity, Guilin 541004, China and Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway NSW 2007, Australia;School of Maths and Computing, Guangxi Normal Univiersity, Guilin 541004, China;Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway NSW 2007, Australia

  • Venue:
  • Information Sciences—Informatics and Computer Science: An International Journal
  • Year:
  • 2004

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Abstract

There is a challenging man-machine-interface issue in existing association analysis algorithms because they are Apriori-like and the Apriori Algorithm is based on the assumption that users can specify the threshold: minimum-support. It is impossible that users give a suitable minimum-support for a database to be mined if the users are without knowledge concerning the database. In this paper, we propose a fuzzy mining strategy with database-independent minimum-support, which provides a good man-machine interface that allows users to specify the minimum-support threshold without any knowledge concerning their databases to be mined. We have evaluated the proposed approach and the experimental results have demonstrated that our algorithm is promising and efficient.