Users shopping behavior mining of B2C e-commerce

DOI

10.2991/icsem.2013.127How to use a DOI?

Keywords

B2C e-commerce, Users shopping behavior, Data mining, Basket model

Abstract

Rich transaction information and customer data can be recorded by the back-end database of e-commerce sites. By the application of the basket model in data mining analysis the correlation between data and predict customer loyalty. Then combined with the customer's shopping behavior, sales promotions pattern based prediction model is proposed and implemented. The research results will enable the B2C e-commerce to make the appropriate commercial promotion, and to improve the profitability of the company in the B2C mode by customer behavior, personal preferences.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ping Gan
PY  - 2013/04
DA  - 2013/04
TI  - Users shopping behavior mining of B2C e-commerce
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 632
EP  - 635
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.127
DO  - 10.2991/icsem.2013.127
ID  - Gan2013/04
ER  -