International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Association rule mining is an active data mining research area. In recent years, association rules from large databases have received considerable attention and have been applied to various areas such as marketing, retail and finance, etc. The traditional algorithms for mining frequent association patterns suffer from the problems of under prediction and over prediction of patterns. The main aim of the present paper is to develop a soft set approach for mining fuzzy quantitative association patterns in order to address the issues of under prediction and over prediction of these patterns.