ABSTRACT

Data mining is a process of discovering fascinating designs, new instructions and information from large amount of sales facts in transactional and interpersonal catalogs. Since inventory databases, universal product bar codes and scanners, and other such supply chain management technologies have been around for years, the idea of using data to help manage retail operations is not new. However, more recently, the use of data mining to more thoroughly understand patterns of consumer behavior that affect retail operations has become more prevalent. In order to truly understand consumer behavior though, it is beneficial to understand both what they buy and who they are. With this information, we can go beyond traditional inventory management, and craft a much more personalized shopping experience for you. All organizations that collect, store, and analyze data have a responsibility to protect privacy, to guard against misuse and abuse, and to share data only within the constraints of fairly developed and disclosed policies. It will be able to expand and apply effective marketing strategies and in disease identification frequent patterns are generated to discover the frequently occur diseases in a definite area. The conclusion in all applications is some kind of association rules (AR) that are useful for efficient decision making.

Keywords: - Association rule mining, FP growth, decision making