Spatial Clustering Analysis of K-Means Algorithm in the Classification of Bank Card Customers

Abstract:

K-means algorithm is a simple and efficient data mining clustering algorithm. For the current status of the bank card customer relationship management, based on data mining technology, design based on K-means clustering algorithm banking customer classification system. Data mining techniques can extract vast amounts of customer information data bank card implicit knowledge and spatial relationship model will represent the bank customers feature set of data objects automatically classified into each composed of clusters of similar objects, bank card customers in the banking system classification. This paper analyzes the existing spatial clustering methods summary and conclusion, based on the combined data bank card customers, according to the volatility of funds used to different customer groups, the use of K-means analysis to study characteristics of client groups, providing appropriate financial services.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 1274-1277
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.1274
• Online since: November 2014
• Authors: Kang Lv*
• Keywords: Classification, K-Means, Spatial Cluster

References

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