Profit Pattern Mining Using Soft Computing for Decision Making

Abstract

Problem of decision making is a crucial task in every business. Profit Pattern Mining hit the target by minimizes the gap between statistical based pattern generation and value base decision making. But this job is found very difficult when it depends on the large, imprecise and vague environment, which is frequent in recent years. The concept of soft computing with data mining is novel way to address this difficulty. The general approaches to association rule mining focus on inducting rule by using correlation among data and finding frequent occurring patterns. The major technique uses support and confidence measures for generating rules which is not adequate nowadays as a measure of interest, since the data have become more multifaceted these days, it's a necessary to find solution that deals with such problems and uses some new measures like profit, significance etc. In this chapter, authors apply concept of pattern mining with vague set theory, Genetic algorithm theory and related properties to the commercial management to deal with business decision making problem.