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IFIP12
2008

Mining Fuzzy Association Rules from Composite Items

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Mining Fuzzy Association Rules from Composite Items
This paper presents an approach for mining fuzzy Association Rules (ARs) relating the properties of composite items, i.e. items that each feature a number of values derived from a common schema. We partition the values associated to properties into fuzzy sets in order to apply fuzzy Association Rule Mining (ARM). This paper describes the process of deriving the fuzzy sets from the properties associated to composite items and a unique Composite Fuzzy Association Rule Mining (CFARM) algorithm founded on the certainty factor interestingness measure to extract fuzzy association rules. The paper demonstrates the potential of composite fuzzy property ARs, and that a more succinct set of property ARs can be produced using the proposed approach than that generated using a nonfuzzy method.
M. Sulaiman Khan, Maybin K. Muyeba, Frans Coenen
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where IFIP12
Authors M. Sulaiman Khan, Maybin K. Muyeba, Frans Coenen
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