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2008

Fuzzy Association Rule Reduction Using Clustering In Som Neural Network

8 years 11 months ago
Fuzzy Association Rule Reduction Using Clustering In Som Neural Network
The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many association rules are obtained, the usefulness of them will be reduced. In this paper, we introduce an approach to reduce and summarize the extracted fuzzy association rules after fuzzy data mining. In our approach, in first, we encode each obtained fuzzy association rule to a string of numbers. Then we use self-organizing map (SOM) neural network iteratively in a tree structure for clustering these encoded rules and summarizing them to a smaller collection of fuzzy association rules. This approach has been applied on a data base containing information about 5000 employees and has shown good results. KEYWORDS Fuzzy Data Mining, Rule Reduction, SOM.
Marjan Kaedi, Mohammad Ali Nematbakhsh, Nasser Gha
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where IADIS
Authors Marjan Kaedi, Mohammad Ali Nematbakhsh, Nasser Ghasem-Aghaee
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