A fast algorithm for mining temporal association rules based on a new definition
Zhan Li, Fusheng Yu, Huixin Zhang · 2017
In literatures, there were several forms of definitions for temporal association rules which have different formulas for calculating support and confidence. In this paper, after reviewing the literatures, we first reform the definition of the association rule, and then give a general form of temporal association rule which was equipped with new formula for calculating its support and confidence. Based on the new definition, we propose a fast algorithm for mining temporal association rules. Experiments on a synthetic dataset and a real dataset exhibit the good performance of the new proposed algorithm.