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Analysis of Book Sales Transaction using Association Rules Mining

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dc.contributor.author Zin, Ei Phyu
dc.contributor.author Aye, Nilar
dc.date.accessioned 2019-07-31T14:21:49Z
dc.date.available 2019-07-31T14:21:49Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1534
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.subject Data Mining en_US
dc.subject Association Rule Mining en_US
dc.subject Market Basket en_US
dc.subject Apriori algorithm en_US
dc.title Analysis of Book Sales Transaction using Association Rules Mining en_US
dc.type Article en_US


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