Mining Temporal Fuzzy Utility Itemsets by Tree Structure
Tzung‐Pei Hong, Chengyu Lin, Wei-Ming Huang, Shu-Min Li, Shyue-Liang Wang, Jerry Chun‐Wei Lin · 2019
More complicated than fuzzy data mining, temporal fuzzy utility data mining takes into account the temporal factor of transactions, purchased quantities, item profits, and linguistic terms. In this paper, a tree structure modified from the frequent-pattern tree is designed and a mining algorithm based on it was proposed to extract high temporal fuzzy utility patterns from transactional datasets with the temporal property. The method requires two-phase processing to find all high temporal fuzzy utility itemsets. Experimental results show that the proposed algorithm performs better than the Apriori-based mining algorithm.