Commodity Recommendation System of E-Commerce Based on Classification Users

Jie Chen

doi:10.4028/www.scientific.net/AMM.556-562.6689

Paper Titles

A Study of Inventory Management in Supply Chain under the Environment of Internet of Things
p.6673

Design of Sharing Multimedia Teaching System in Practical Education of PE
p.6677

The Design and Realization of University Library Personalized Service Based on Date-Mining Technology
p.6681

Design and Implementation of Information Management System Based on Cloud Computing Mode
p.6685

Commodity Recommendation System of E-Commerce Based on Classification Users
p.6689

Researches on Virtual Enterprise Customer Relationship Management Technology
p.6693

Design of Flexible Contingency Plan Management System
p.6698

The Development and Application of Digita Experiment Teaching Platform
p.6703

Design of Urban Emergency System Based on 3S Spatial Information Technology
p.6707

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Commodity Recommendation System of E-Commerce...

Commodity Recommendation System of E-Commerce Based on Classification Users

Abstract:

With the development of electronic commerce, commodity recommendation system of using a single strategy for all users has been unable to meet the needs of businesses and consumers. This paper proposed a commodity recommendation strategy of e-commerce based on classification users, e-commerce users are classified as new users, general users, Silver users and Gold users. According to the difference of users, the paper recommended using different methods to improve the efficiency of commodity recommendation system to better meet user needs.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

6689-6692

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.6689

Citation:

Cite this paper

Online since:

May 2014

Authors:

Jie Chen*

Keywords:

Classification Users, Collaborative Filtering (CF), Commodity Recommendation, MDP, Preferences Mining

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Xu M, Qiu Y H and Qiu J: Segmenting your users in recommender system, Proceeding of the IASTED International Conference, Modeling and Simulation (2003).

Google Scholar

[2] Yi Xie, Deren Chen and Honghua Gan: Journal of Computer Applications (2011), In Chinese.

Google Scholar

[3] Hongxia Zhao, Xinhai Wang and Jiaoping Yang: Application Research of Computers (2011), In Chinese.

Google Scholar

[4] Wei Chen, Lijun Zhang and Chun Chen: a hybrid phonic web news recommender system for pervasive access, International Conference on Communications and Mobile Computing (2009).

DOI: 10.1109/cmc.2009.20

Google Scholar

[5] Guy Shani, David Heckerman and Ronen Brafman: Journal of Machine Learning Research (2005).

Google Scholar