Proceedings of the 2016 International Conference on Education, Management, Computer and Society

Application of Data Mining Technology in Intelligent Electronic Commerce Search and Recommendation

Authors
Xue Bai
Corresponding Author
Xue Bai
Available Online January 2016.
DOI
10.2991/emcs-16.2016.96How to use a DOI?
Keywords
Data mining; Electronic Commerce; Personalized recommendation; Search; Intelligent
Abstract

Personalized recommendation technology is the core and key technology in the electronic commerce recommendation system. Data mining technology can help decision makers to find out the potential relationship between the data and find out the potential relationship among the data. This paper firstly analyzes the application of intelligent electronic commerce search and personalized recommendation, and presents application of data mining technology and intelligent agent in e-commerce recommendation system. Finally, the paper presents the application of data mining technology in intelligent e-commerce search and recommendation.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 International Conference on Education, Management, Computer and Society
Series
Advances in Computer Science Research
Publication Date
January 2016
ISBN
10.2991/emcs-16.2016.96
ISSN
2352-538X
DOI
10.2991/emcs-16.2016.96How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Xue Bai
PY  - 2016/01
DA  - 2016/01
TI  - Application of Data Mining Technology in Intelligent Electronic Commerce Search and Recommendation
BT  - Proceedings of the 2016 International Conference on Education, Management, Computer and Society
PB  - Atlantis Press
SP  - 400
EP  - 404
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-16.2016.96
DO  - 10.2991/emcs-16.2016.96
ID  - Bai2016/01
ER  -