Trust Metrics in Recommender Systems-Reference-Cited by-同舟云学术

Trust Metrics in Recommender Systems

Published:2009 Issue: Volume: Page:259-285
ISSN:1571-5035
Container-title:Human–Computer Interaction Series
language:
Short-container-title:

Author:

Massa Paolo,Avesani Paolo

Publisher

Springer London

Link

http://link.springer.com/content/pdf/10.1007/978-1-84800-356-9_10

Reference26 articles.

1. P. Resnick and H. Varian. Recommender systems. Communications of the ACM, 40(3):56–58, 1997.

2. J. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth Conference on Uncertainty in Artifi cial Intelligence, Madison, WI, July 1998. Morgan Kaufmann.

3. A. Toffler. Future shock, 1970. Random House, New York.

4. J.B. Schafer, J. Konstan and J. Riedl. Recommender Systems in E-Commerce. Proceeding of the ACM Conference on Electronic Commerce, Pittsburgh, PA, USA, 1999

5. M. P. O’Mahony, N. J. Hurley, and G. C. M. Silvestre. Recommender systems: Attack types and strategies. In Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-05), Pittsburgh, Pennsylvania, USA, 9–13, Jul 2005. AAAI Press.

Cited by 87 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated Conversational Recommender Systems;Lecture Notes in Computer Science;2024

2. An enhanced attentive implicit relation embedding for social recommendation;Data & Knowledge Engineering;2023-05

3. IcaGCN: Model Intents via Coactivated Graph Convolution Network for Recommendation;IEEE Access;2023

4. A Survey of Explainable E-Commerce Recommender Systems;2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT);2022-11

5. ImposeSVD: Incrementing PureSVD For Top-N Recommendations for Cold-Start Problems and Sparse Datasets;The Computer Journal;2022-08-02