Exploring Longitudinal Effects of Session-based Recommendations
Author:
Affiliation:
1. Music Technology Group - Universitat Pompeu Fabra, Spain
2. AAU Klagenfurt, Austria
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3383313.3412213
Reference23 articles.
1. Controlling Popularity Bias in Learning-to-Rank Recommendation
2. Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques
3. Automated Generation of Music Playlists: Survey and Experiments
4. Pablo Castells Neil J. Hurley and Saul Vargas. 2015. Novelty and Diversity in Recommender Systems. In Recommender Systems Handbook Francesco Ricci Lior Rokach and Bracha Shapira (Eds.). 881–918. Pablo Castells Neil J. Hurley and Saul Vargas. 2015. Novelty and Diversity in Recommender Systems. In Recommender Systems Handbook Francesco Ricci Lior Rokach and Bracha Shapira (Eds.). 881–918.
5. How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
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