Finding Associations in Composite Data Sets: The CFARM Algorithm

摘要

In this paper a composite fuzzy association rule mining mechanism (CFARM), directed at identifying patterns in datasets comprised ofcomposite attributes, is described. Composite attributes are defined as attributes that can take simultaneously two or more values that subscribe to a common schema. The objective is to generate fuzzy association rules using "properties" associated with these composite attributes. The exemplar applica-tion is the analysis of the nutrients contained in items found in grocery data'sets. The paper commences with a review of the back ground and related work and a formal definition of the CFARM concepts. The CFARM algorithm is then fully described and evaluated using both real and synthetic data sets.