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. |
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