Personalized diffusions for top-n recommendation

Author:

Nikolakopoulos Athanasios N.1,Berberidis Dimitris1,Karypis George1,Giannakis Georgios B.1

Affiliation:

1. University of Minnesota

Funder

National Science Foundation

Army Research Office

Intel Corporation

Publisher

ACM

Cited by 10 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. Contextual MAB Oriented Embedding Denoising for Sequential Recommendation;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04

2. A Revisiting Study of Appropriate Offline Evaluation for Top- N Recommendation Algorithms;ACM Transactions on Information Systems;2022-12-21

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

4. The Datasets Dilemma;Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining;2022-02-11

5. DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation;IEEE Transactions on Pattern Analysis and Machine Intelligence;2022

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