Improved Precision Recommendation Scheme by BPNN Algorithm in O2O Commerce

Author

Yen-Chiu Chen ; Hui-Ching Hsieh ; He-Chih Lin

Author_Institution

Inf. & Commun. Res. Labs. (ICL), Ind. Technol. Res. Inst. (ITRI), Hsinchu, Taiwan

fYear

2013

fDate

11-13 Sept. 2013

Firstpage

324

Lastpage

328

Abstract

Online to Offline (O2O) commerce is a newly business model between company and customers. Under such environment, it is very important to recommend some useful and precise advertisement for users. If the recommendation work is down, it will attract more users to pay online and then get the related products in the real-world stores (offline). In this paper, we proposed a methodology based on the Back Propagation Neural Network algorithm to recommend some real-world store information for users. The results are more precise and close to users´ desires.

Keywords

advertising data processing; backpropagation; electronic commerce; neural nets; recommender systems; BPNN algorithm; O2O commerce; advertisement; back propagation neural network algorithm; business model; online to offline commerce; precision recommendation scheme; real-world store information; Artificial neural networks; Companies; Global Positioning System; Prediction algorithms; Vectors; O2O; neural network; online to offline; recommendation system;

fLanguage

English

Publisher

ieee

Conference_Titel

e-Business Engineering (ICEBE), 2013 IEEE 10th International Conference on

Conference_Location

Coventry

Type

conf

DOI

10.1109/ICEBE.2013.50

Filename

6686283