@article {343,
	title = {A new customer classification algorithm for electronic commerce enterprises},
	journal = {Journal of Digital Information Management},
	volume = {10},
	year = {2012},
	note = {Export Date: 10 July 2014},
	month = {2012},
	pages = {284 - 288},
	abstract = {Correctly and effectively customer classification according to their characteristics and behaviors will be the most important resource for electronic marketing and online trading of network enterprises. A new customer classification algorithm for electronic commerce enterprises is advanced based on analyzing customer characteristics and behaviors. First, based on consumer characteristics and behavior analysis, 21 customer classification indicators, including customer characteristics type variables and customer behavior type variables, are designed, Second, aiming at the shortages of the existing BP neural network algorithm of data-mining for customer classification, the immune-genetic algorithm is used to correct BP neural network to speed up the convergence of the model. Finally the experimental results verify that the new algorithm can improve customer classification accuracy and can guarantee the effectiveness and validity of customer classification for electronic commerce enterprises in its engineering application.},
	keywords = {BP Neural Network, Customer classification, Electronic commerce, Immune genetics},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84870801373\&partnerID=40\&md5=e0e9cd1f8a408b64aa0f9dc6037ec8e6},
	author = {Li, X.}
}
