Curse of "Low" Dimensionality in Recommender Systems

Author:

Ohsaka Naoto1ORCID,Togashi Riku1ORCID

Affiliation:

1. CyberAgent, Inc., Tokyo, Japan

Publisher

ACM

Reference70 articles.

1. Controlling Popularity Bias in Learning-to-Rank Recommendation

2. Himan Abdollahpouri , Robin Burke , and Bamshad Mobasher . 2019 . Managing popularity bias in recommender systems with personalized re-ranking . In International FLAIRS Conference. Himan Abdollahpouri, Robin Burke, and Bamshad Mobasher. 2019. Managing popularity bias in recommender systems with personalized re-ranking. In International FLAIRS Conference.

3. Gediminas Adomavicius and YoungOk Kwon . 2009 . Toward more diverse recommendations: Item re-ranking methods for recommender systems . In Workshop on Information Technologies and Systems. Citeseer, 79--84 . Gediminas Adomavicius and YoungOk Kwon. 2009. Toward more diverse recommendations: Item re-ranking methods for recommender systems. In Workshop on Information Technologies and Systems. Citeseer, 79--84.

4. Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

5. Optimization-Based Approaches for Maximizing Aggregate Recommendation Diversity

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