UTARM: an efficient algorithm for mining of utility-oriented temporal association rules

Abstract

Recently, association rule mining has become an area of interest for research in the field of knowledge discovery and several algorithms have been established. Lately, for business development, data mining researchers have enhanced the quality of association rule mining for the mining of association patterns by integrating the influential factors, for instance temporal, value (utility) and more. Here, we have proposed an efficient algorithm, called UTARM (Utility-Based Temporal Association Rule Mining), which combines both temporal (time periods) and utility for mining of remarkable and helpful association rules. The proposed algorithm can be able to mine utility-oriented temporal association rules by adapting the support with relevant to the time periods and utility. Furthermore, the scan time required for finding the FTU itemsets is considerably reduced. The experimentation is carried out on large data sets and the experimental results ensure that the proposed algorithm effectively discovers the utility-oriented temporal association rules.