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Clustering and Pattern Mining of Customer Transaction Data using Apriori Algorithm
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Clustering customer transaction data is an important procedure for analyzing customer behavior in retail and e-Commerce. Clustering of trading data with finding patterns using Apriori algorithm will helps to develop a market strategy and increases the profit. The system uses Apriori algorithm for finding pattern. The input of Apriori algorithm is the output of Customer Transaction Clustering Algorithm. In a system the customer transaction data is presented by using transaction tree and the distance between them is also calculated. Cluster the customer transaction data by using customer transaction clustering algorithm. The system selects frequent customer as representatives of customer groups. Finally, the system forwards the output of clustering to Apriori algorithm for finding patterns.
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Title: Clustering and Pattern Mining of Customer Transaction Data using Apriori Algorithm
Description:
Clustering customer transaction data is an important procedure for analyzing customer behavior in retail and e-Commerce.
Clustering of trading data with finding patterns using Apriori algorithm will helps to develop a market strategy and increases the profit.
The system uses Apriori algorithm for finding pattern.
The input of Apriori algorithm is the output of Customer Transaction Clustering Algorithm.
In a system the customer transaction data is presented by using transaction tree and the distance between them is also calculated.
Cluster the customer transaction data by using customer transaction clustering algorithm.
The system selects frequent customer as representatives of customer groups.
Finally, the system forwards the output of clustering to Apriori algorithm for finding patterns.
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