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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jian Shi Junyun Chen Zhuolan Bao |
| Copyright Year | 2011 |
| Description | Author affiliation: Research Center of Corporate Governance of Nankai University, Business School of Nankai University, Tianjin, China (Jian Shi; Junyun Chen; Zhuolan Bao) |
| Abstract | Driven by information technology, e-commerce has made rapid development on a global scale, particularly in China. However, while the rapid development of e-commerce continues to meet people's needs shopping online, it also puts people into the information ocean. Therefore, e-commerce platforms need an automated shopping assistant to help people reduce the cost of shopping, decrease the time spent on shopping and make it interesting. Recommender system is undoubtedly the best option. In this paper, we first summarize the present literature of recommender system and the main technical aspects of it, Mainly include the technology used in recommender system, the main recommendation technology, systems evaluation method and collaborative filtering algorithm, and then present the current problems and present solutions to the comb, with the wish that it can promote future research. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 281203 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781612843100 |
| ISSN | 21611890 |
| e-ISBN | 9781612843117 |
| DOI | 10.1109/ICSSSM.2011.5959336 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | collaborative filtering Correlation recommender system Bayesian methods Collaboration Clustering algorithms Prediction algorithms e-commerce Recommender systems |
| Content Type | Text |
| Resource Type | Article |
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