Customer Behavior Pattern Discovering Based on Mixed Data Clustering

To be effective to retain customers and enhance the marketing capabilities, it is necessary to improve the personalization of e-commerce systems. Clustering is a reliable and efficient technology to provide personal service in e-commerce system. However, current research on clustering algorithm usually based on numeric data or categorical data. To analysis customer behavior, mixed data set must be handled. With extending the ROCK algorithm, a novel method to deal with mixed data set was proposed and experiment shows the new algorithm is efficient and successful.