An Analysis of Web Mining-based Recommender Systems for E-commerce

DOI

10.2991/iccasm.2012.43How to use a DOI?

Keywords

E-commerce, Clustering, Recommender Systems, and Personalized Services

Abstract

This article proposes a framework of Web miningbased recommender systems for e-commerce. Building on clustering analysis of data involving Web usage, content and structure, the author demonstrates how to provide users with effective recommender services according to the mining results obtained by recommender engine. Finally, the author reaches his conclusion of the advantages and practicalities of Web mining-based recommender systems for e-commerce.

Copyright

© 2012, 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/).

Download article (PDF)

TY  - CONF
AU  - Ya Luo
PY  - 2012/08
DA  - 2012/08
TI  - An Analysis of Web Mining-based Recommender Systems for E-commerce
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 167
EP  - 170
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.43
DO  - 10.2991/iccasm.2012.43
ID  - Luo2012/08
ER  -