Applying improved clustering algorithm into EC environment data mining
JiangTong Hai; MaYu Peng
2014
会议名称2nd International Conference on Mechatronics and Industrial Informatics, ICMII 2014
会议日期May 30, 2014 - May 31, 2014
会议地点Guangzhou, China
页码951-959
中文摘要With the rising growth of electronic commerce (EC) customers, EC service providers are keen to analyze the on-line browsing behavior of the customers in their web site and learn their specific features. Clustering is a popular non-directed learning data mining technique for partitioning a dataset into a set of clusters. Although there are many clustering algorithms, none is superior for the task of customer segmentation. This suggests that a proper clustering algorithm should be generated for EC environment. In this paper we are concerned with the situation and proposed an improved k-means algorithm, which is effective to exclude the noisy data and improve the clustering accuracy. The experimental results performed on real EC environment are provided to demonstrate the effectiveness and feasibility of the proposed approach.
收录类别EI
会议录出版地Trans Tech Publications Ltd
语种英语
ISSN号16609336
ISBN号9783038351764
内容类型会议论文
源URL[http://ir.xjipc.cas.cn/handle/365002/3611]  
专题新疆理化技术研究所_多语种信息技术研究室
推荐引用方式
GB/T 7714
JiangTong Hai,MaYu Peng. Applying improved clustering algorithm into EC environment data mining[C]. 见:2nd International Conference on Mechatronics and Industrial Informatics, ICMII 2014. Guangzhou, China. May 30, 2014 - May 31, 2014.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace