Research on Information Fusion Method of Mobile Commerce based on Monte Carlo Algorithm under Big Data Environment

DOI

10.2991/emcs-17.2017.203How to use a DOI?

Keywords

Big data; Location information; Information fusion; Improved monte carlo algorithm

Abstract

In the large data environment, the amount of mobile e-commerce information increases sharply and highlights the characteristics of users' location. How to utilize the user's location quickly and effectively to find the valuable information of the users and supply them with the decision-making service becomes one of the important subjects of the mobile electronic commerce in recent years. Based on the traditional Monte Carlo algorithm, this paper proposes an improved Monte Carlo algorithm, a fast Monte Carlo algorithm, which can effectively solve the problem of particle degradation in the traditional algorithm. Finally, the simulation experiment is carried out. Compared with the traditional information fusion method, the experiment demonstrates that the fusion method has high accuracy and reduces the complexity of the system algorithm, so that the e-commerce platform can predict the users' behavior information more accurately and can provide decision-making services more appropriately.

Copyright

© 2017, 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  - Tingbin Chen
AU  - Qisong Zhang
AU  - Jingshu Wang
PY  - 2017/03
DA  - 2017/03
TI  - Research on Information Fusion Method of Mobile Commerce based on Monte Carlo Algorithm under Big Data Environment
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 1049
EP  - 1056
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.203
DO  - 10.2991/emcs-17.2017.203
ID  - Chen2017/03
ER  -