Optimization of Association Rules for Students' Data: A Soft Set

Abstract

Association rule (AR) mining is a common method to find the associations between objects in a transaction or in a data set, which is simple logical rules, determine the critical relationship among the objects. The rule generation is difficult if it satisfies a predefined threshold value. To trace the relationship is very important for domains to reveal crucial and hidden information from the data set. Some critical relationship of the objects may appear rarely and to trace them using classical methods are difficult one. The apriori algorithm (AA) with hashing technique along with the PDI algorithm is used to find the appropriate ARs from the students’ dataset. Since soft set is a tool for handling imprecise parameterized data, the soft set concept is used in optimization process to get optimized ARs. In this paper, the ARs are optimized using soft set for further analysis.