DMCA
A Graph Model for E-Commerce Recommender Systems (2004)
| Venue: | Journal of the American Society for Information Science and Technology |
| Citations: | 36 - 7 self |
BibTeX
@ARTICLE{Huang04agraph,
author = {Zan Huang and Wingyan Chung and Hsinchun Chen},
title = {A Graph Model for E-Commerce Recommender Systems},
journal = {Journal of the American Society for Information Science and Technology},
year = {2004},
volume = {55},
pages = {259--274}
}
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Abstract
this article, we review previous research in recommender systems to identify frequently used approaches and representations. Four recommendation approaches were examined: knowledge engineering, collaborative filtering, a content-based approach, and a hybrid approach. Different recommendation approaches can be implemented using different analytical methods. Commonly used methods are neighborhood formation, association rule mining, machine learning techniques, etc
Keyphrases
graph model e-commerce recommender system knowledge engineering hybrid approach neighborhood formation collaborative filtering different recommendation approach content-based approach recommender system recommendation approach previous research different analytical method association rule mining
