Association Rules for Predicting Customer Lifetime Value in Retail Banking Context Based on RDB- MINER Algorithm
نویسنده
چکیده
Data mining methodology has a tremendous contribution for extracting the hidden knowledge and patterns from the existing databases. Traditionally, researchers use basket data to mine association rules of which the basic task is to find the frequent items. For relational databases whose data format is relational data other than basket data, RDB-MINER algorithm was proposed. In this paper, we introduce an improved RDBMINER algorithm and apply it to mine association rules in retail banking relational databases. When we assess the customer lifetime value, RFM model is adopted. Moreover, we propose a method to find the association rules between customers’ attributes and their lifetime value, these patterns are significant for predicting their future value. KeywordsAssociation Rules; Customer Lifetime Value; Relational Database; RDB-MINER Algorithm; RFM Model; Retail Banking.
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