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Received:October 30, 2009 Revised:December 18, 2009
Received:October 30, 2009 Revised:December 18, 2009
中文摘要: 传统的蚁群聚类算法需设置较多参数，且聚类时间较长。基于信息熵的蚁群聚类算法通过信息熵改变蚂蚁拾起和放下数据的规则，减少了参数的设置、缩短了聚类的时间，将其应用于客户细分，并且与采用传统的蚁群聚类算法得到的细分结果进行比较分析，实验表明。基于信息熵的蚁群聚类算法可以加快客户细分的聚类进程。
Abstract:The ant-based clustering algorithm needs to set several parameters and cluster for a long time.The ant- based clustering algorithm based on entropy, which uses entropy to amend the ants picking and dropping rules, can reduce the number of parameters and shorten the time of clustering. This paper intends to apply it to the customer segmentation, and compares the segmentation results with the traditional ant-based clustering algorithm. The experiment shows that the ant-based clustering algorithm based on entropy can accelerate customer segmentation.
文章编号： 中图分类号： 文献标志码：
基金项目:安徽省自然科学基金(090416240);高等学校优秀青年人才基金(2009SQRS001ZD)
| Author Name | Affiliation |
| WU Chun-Xu | 中国科学技术大学 管理学院 安徽 合肥 230026 |
| LIU Yan-Ze | |
| GOU Qing-Long |
| Author Name | Affiliation |
| WU Chun-Xu | 中国科学技术大学 管理学院 安徽 合肥 230026 |
| LIU Yan-Ze | |
| GOU Qing-Long |
引用文本：
吴春旭,刘艳泽,苟清龙.基于信息熵的蚁群聚类算法在客户细分中的应用①.计算机系统应用,2010,19(7):171-174
WU Chun-Xu,LIU Yan-Ze,GOU Qing-Long.Ant Colony Algorithm Based on Entropy for Customer Segmentation.COMPUTER SYSTEMS APPLICATIONS,2010,19(7):171-174
吴春旭,刘艳泽,苟清龙.基于信息熵的蚁群聚类算法在客户细分中的应用①.计算机系统应用,2010,19(7):171-174
WU Chun-Xu,LIU Yan-Ze,GOU Qing-Long.Ant Colony Algorithm Based on Entropy for Customer Segmentation.COMPUTER SYSTEMS APPLICATIONS,2010,19(7):171-174
