A genetic-fuzzy mining approach for items with multiple minimum supports

Chun Hao Chen, Tzung Pei Hong*, S. Tseng, Chang Shing Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions under a single minimum support. In real applications, different items may have different criteria to judge their importance. In this paper, we thus propose an algorithm which combines clustering, fuzzy and genetic concepts for extracting reasonable multiple minimum support values, membership functions and fuzzy association rules form quantitative transactions. It first uses the k-means clustering approach to gather similar items into groups. All items in the same cluster are considered to have similar characteristics and are assigned similar values for initializing a better population. Each chromosome is then evaluated by the criteria of requirement satisfaction and suitability of membership functions to estimate its fitness value. Experimental results also show the effectiveness and the efficiency of the proposed approach.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Fuzzy Systems, FUZZY
DOIs
StatePublished - 1 Dec 2007
Event2007 IEEE International Conference on Fuzzy Systems, FUZZY - London, United Kingdom
Duration: 23 Jul 200726 Jul 2007

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2007 IEEE International Conference on Fuzzy Systems, FUZZY
CountryUnited Kingdom
CityLondon
Period23/07/0726/07/07

Fingerprint Dive into the research topics of 'A genetic-fuzzy mining approach for items with multiple minimum supports'. Together they form a unique fingerprint.

  • Cite this

    Chen, C. H., Hong, T. P., Tseng, S., & Lee, C. S. (2007). A genetic-fuzzy mining approach for items with multiple minimum supports. In 2007 IEEE International Conference on Fuzzy Systems, FUZZY [4295628] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2007.4295628