基于3DM的B2C客户分类算法

任何高效的客户关系管理都是以扎实的客户分类为基础,然而电子商务中所搜集到的客户信息往往具有海量、高维度和不完备等特点,传统的客户分类方法很难适合B2C客户数据的分类.研究表明,数据挖掘的实质是知识在不同形态下的转换过程,面向领域的数据驱动的数据挖掘理论(3DM)能将领域知识、先验知识和数据本身的特点有机结合.以电子商务B2C客户数据为例,设计了基于3DM的客户分类算法,通过实例表明,该算法能较好地解决B2C客户数据的分类问题.

3DM based customer classification algorithm of B2C

Any efficient customer relationship management is based on the excellent classification of customers. However, the correlated information of e-commerce customers is always huge, multi-dimension and incomplete, and it is hard to classify customers properly. The study shows that the essence of data mining is a knowledge transformation process in different formats. Thus, a data mining process is not only mining knowledge from data, but also from human. Domain oriented data driven data mining (3DM) can combine prior domain knowledge, user''s interest and user''s constraint with data sets effectively. According to the traits of e-commerce customers, a model of B2C customer classification was proposed in this paper. Furthermore, a new 3DM based algorithm was put forward, and the simulation results show its validity.