Searching of interesting itemsets for negative association rules

TL;DR

This paper introduces a new algorithm that efficiently searches for both positive and negative itemsets of interest, enabling comprehensive mining of all types of association rules.

Contribution

The proposed algorithm addresses the limitations of traditional methods by including negative itemsets, facilitating complete negative and positive association rule mining.

Findings

Successfully searches for both positive and negative itemsets

Enables comprehensive mining of association rules

Reduces search space compared to traditional algorithms

Abstract

In this paper, we propose an algorithm of searching for both positive and negative itemsets of interest which should be given at the first stage for positive and negative association rules mining. Traditional association rule mining algorithms extract positive association rules based on frequent itemsets, for which the frequent itemsets, i.e. only positive itemsets of interest are searched. Further, there are useful itemsets among the frequent itemsets pruned from the traditional algorithms to reduce the search space, for mining of negative association rules. Therefore, the traditional algorithms have not come true to find negative itemsets needed in mining of negative association rules. Our new algorithm to search for both positive and negative itemsets of interest prepares preconditions for mining of all positive and negative association rules.