Comparative Analysis of Single and Multiple Minimum Support Based Association Rule Mining Algorithms

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Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Data Management
Format: PDF
Association rule mining techniques discover associations between entities. Some techniques are single minimum support based while some are multiple minimum support based. Single minimum support based approach suffer from rare item problem dilemma while multiple support based approach considers rare items for mining association rules. In this paper the authors have evaluated performance of Apriori-T and MSApriori-T algorithms that are single and multiple minimum based approaches respectively. These algorithms use an efficient data storage mechanism total support tree for storing item sets.
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