Recommender Systems as Multistakeholder Environments-Reference-Cited by-同舟云学术

Recommender Systems as Multistakeholder Environments

Published:2017-07-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization
language:
Short-container-title:

Author:

Abdollahpouri Himan¹,Burke Robin¹,Mobasher Bamshad¹

Affiliation:

1. DePaul University, Chicago, IL, USA

Funder

NSF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3079628.3079657

Reference17 articles.

1. Click shaping to optimize multiple objectives

2. David Evans Richard Schmalensee Michael Noel Howard Chang and Daniel Garcia-Swartz. 2011. Platform economics: Essays on multi-sided businesses. Competition Policy International. David Evans Richard Schmalensee Michael Noel Howard Chang and Daniel Garcia-Swartz. 2011. Platform economics: Essays on multi-sided businesses. Competition Policy International.

3. David S. Evans and Richard Schmalensee. 2016. Matchmakers: The New Economics of Multisided Platforms. Harvard Business Review Press. David S. Evans and Richard Schmalensee. 2016. Matchmakers: The New Economics of Multisided Platforms. Harvard Business Review Press.

Cited by 46 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. A survey on popularity bias in recommender systems;User Modeling and User-Adapted Interaction;2024-07-01

2. Simulation of recommender systems driven tourism promotion campaigns;Information Technology & Tourism;2024-03-30

3. FRS4CPP: A Fair Recommendation Strategy Considering Interests of Users, Providers and Platform;Communications in Computer and Information Science;2024

4. Vertical Allocation-based Fair Exposure Amortizing in Ranking;Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region;2023-11-26

5. A large scale benchmark for session-based recommendations on the legal domain;Artificial Intelligence and Law;2023-10-25