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Mining Frequent Itemsets Based on Tree Structure from Transactional Dataset

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Author Affiliations

  • 1Faculty of Technology & Engineering, C. U. Shah University, Wadhwan City, Gujarat, India
  • 2RDI Centre, C. U. Shah University, Wadhwan City, Gujarat, India

Res. J. Computer & IT Sci., Volume 12, Issue (1), Pages 1-4, June,20 (2024)

Abstract

Research on mining frequent patterns is one of the emerging task in knowledge discovery. Many researchers have been studied efficient frequent itemset finding methods. All the previously available algorithms for mining frequent itemsets from transactional dataset are not efficient. The efficiency of algorithms is dependent on process of candidates generation, the structure which is used for storing generated candidates and the implementation. In this study, we propose a newly discovered Frequent Itemset Tree (FI-Tree) data structure. It is used for stowing frequent itemsets and its associated Transaction ID sets. In several data characteristics, MFIBT have a unique feature is that it has runs speedy. Our study shows that a MFIBT has better performs in terms of run time and memory consumption on transactional dataset.

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