COMPARATIVE STUDY OF IMPROVED ASSOCIATION RULES MINING BASED ON SHOPPING SYSTEM
Keywords:
Comparative Study, Association Rule Mining, FP Growth, Decision MakingAbstract
Data mining is a process of discovering fascinating designs, new instructions and information from large amount of sales facts in transactional and interpersonal catalogs. The main purpose of this function is to find frequent patterns, associations and relationship between various database using different Algorithms. Association rule mining (ARM) is used to improve decisions making in the applications. ARM became essential in an information- and decision-overloaded world. They changed the way users make decisions, and helped their creators to increase revenue at the same time. Bringing ARM to a broader audience is essential in order to popularize them beyond the limits of scientific research and high technology entrepreneurship. 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.
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