A Regularized Model to Trade-off between Accuracy and Diversity in a News Recommender System-Reference-Cited by-同舟云学术

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A Regularized Model to Trade-off between Accuracy and Diversity in a News Recommender System

Published:2020-12-10 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Big Data (Big Data)
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Author:

Raza Shaina,Ding Chen

Funder

Science and Engineering Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9377717/9377728/09378340.pdf?arnumber=9378340

Cited by 18 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. Evaluating Group Fairness in News Recommendations: A Comparative Study of Algorithms and Metrics;Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization;2024-06-27

2. Examining factors influencing the user’s loyalty on algorithmic news recommendation service;Humanities and Social Sciences Communications;2024-01-02

3. Bias Reduction News Recommendation System;Digital;2023-12-28

4. Recommender Systems: Techniques, Effects, and Measures Toward Pluralism and Fairness;Introduction to Digital Humanism;2023-12-21

5. Deep learning in news recommender systems: A comprehensive survey, challenges and future trends;Neurocomputing;2023-12

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