International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Frequent item set mining is a heart favorite topic of research for many researchers over the years. It is the basis for association rule mining. Association rule mining is used in many applications like: market basket analysis, intrusion detection, privacy preserving, etc. In this paper, the authors have developed a method to discover large item sets from the transaction database. The proposed method is fast in comparison to older algorithms. Also it takes les main memory space for computation purpose.