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Vol. 4,  Special Issue(Bi-yearly) -  Paper Submission  Deadline: 20th  December 2019


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PATTERN MINING USING APRIORI ALGORITHM AFTERCLUSTERING OF CUSTOMER TRANSACTION DATA 

Abstract

Abstract: Clustering of customer transactiondata and finding patterns using Apriori Algorithm is useful task in data miningto formulate market strategies and maximize profit. The system applies anApriori Algorithm for finding patterns. This system use output of CustomerTransaction Clustering Algorithm as an input to Apriori Algorithm. The systemhave transaction tree which represents the customer's transaction records.  Distance between transaction trees iscalculated. A customer transaction clustering algorithm is used for clusteringof transaction data of customers. The most frequent customers are selected asrepresentatives of customer groups. Clustering is performed by assigningcustomer to the nearest neighborhood. Finally, the clustering results areforwarded to Apriori Algorithm for finding patterns.

Keywords - Customer TransactionClustering Algorithm, Apriori Algorithm, Transaction Tree, Clustering.

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IMPACT FACTOR: 5.909(2018)

IMPACT FACTOR: 4.109(2017)
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Organized  National Conference on  SUSTAINABLE SOLID WASTE MANAGEMENT (SSWM)

@ AMITY SCHOOL OF ENGINEERING & TECHNOLOGY

Department of Civil Engineering,

Amity University Haryana,


&

  CSEEEC-2019       

  National Computer Science ,Electronics, Electrical  Engineering Conference 



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