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dc.contributor.authorKumar, P.-
dc.contributor.authorAnanthanarayana, V.S.-
dc.date.accessioned2020-03-30T10:02:43Z-
dc.date.available2020-03-30T10:02:43Z-
dc.date.issued2010-
dc.identifier.citation2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010, 2010, Vol.5, , pp.718-722en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7741-
dc.description.abstractMining of association rules for basket databases, has been investigated by [1] [3] [4], [9], [12], etc. Most of these works focus on mining binary association rules, i.e, most of the association rules mining algorithms to discover frequent itemsets do not consider the quantity in which items have been purchased. This paper discusses an efficient method for discovering a weighted association rules from a large volumes of data in a single scan of the database. The data structure used here is called Weighted Tree. We found that this algorithm is more efficient than Cai's Algorithm. �2010 IEEE.en_US
dc.titleDiscovery of weighted association rules miningen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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