Analysis of Book Sales Transaction using Association Rules Mining

Abstract

Data Mining is the process of analysis of raw data in the database and synthesizing it into information that is useful for effective decision making. Association rule mining finds interesting association or correlation relationships among a large set of data items. The discovery of interesting association relationships among huge amount of business transaction records can help in many business decision making processes. A typical example of association rule mining is market basket analysis. This process analyzes customer buying habits by finding associations between the different items that customers place in their shopping baskets. The discovery of such association can help retailers develop marketing strategies by gaining insight into which items are frequently purchased together by customers. This thesis, is intended to develop a system for market basket analysis on Book Store which will generat strong efficient rules among itemsets with use of Apriori Algorithm.This system will be implemented the Java Programming language.