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Mining Association Rules for Construction Accessories Shop

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dc.contributor.author Thein, Lwin Po Po
dc.contributor.author Nyunt, Kyi Zar
dc.date.accessioned 2019-07-26T06:18:37Z
dc.date.available 2019-07-26T06:18:37Z
dc.date.issued 2011-12-29
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1373
dc.description.abstract In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. Association rules describe events that tend to occur together. Association rules are “if-then rules” with two measures which quantify the support and confidence of the rule for a given data set. This paper describes which products tend to be purchased together at the construction accessories shop. The proposed system has a large database of customer transcation. Each transcation consists of items purchased by a customer in a visit. In this paper, the system ppresents resultws of applying the apriori algorithm which is the standard algorithm to mine association rules for sales data of the construction. en_US
dc.language.iso en en_US
dc.publisher Sixth Local Conference on Parallel and Soft Computing en_US
dc.title Mining Association Rules for Construction Accessories Shop en_US
dc.type Article en_US

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