改进DBSCAN聚类算法在电子商务网站评价中的应用

Journal of Jilin University Science Edition

Application of ECommerce Sites Evaluation withImproved DBSCAN Clustering Algorithm

JIANG Jianhua^1,2，3, YANG Yumian^1,3, BIAN Haiyan^1,3, KANG Jiarong^1,3, WANG Limin^1,3, LIU Ying^1,3

1. School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun 130117, China; 2. Key Laboratory of Logistics Industry Economy and Intelligent Logistics, Jilin University of Finance and Economics, Changchun 130117, China; 3. Jilin Province Key Laboratory of Internet Finance, Jilin University of Finance and Economics, Changchun 130117, China

Received:2014-12-16 Online:2016-03-26 Published:2016-03-23
Contact: JIANG Jianhua E-mail:jjh@jlufe.edu.cn

Abstract

Abstract:

In view of the relevant data of 100 ECommerce demonstration enterprises in China, we first used factor analysis method to reduce the dimension of high dimensional data, then we processed the uneven density data of reduced dimension by using improved DBSCAN (densitybased spatial clustering of applications with noise) algorithm, and obtained more reasonable clustering results. Finally, according to the clustering results, we put forward some suggestions to the relevant enterprises.

Key words: E-commerce sites, factor analysis, DBSCAN algorithm; cluster analysis

CLC Number:

TP391

JIANG Jianhua, YANG Yumian, BIAN Haiyan, KANG Jiarong, WANG Limin, LIU Ying. Application of ECommerce Sites Evaluation withImproved DBSCAN Clustering Algorithm[J].Journal of Jilin University Science Edition, 2016, 54(02): 329-336.

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Application of ECommerce Sites Evaluation withImproved DBSCAN Clustering Algorithm

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