This paper reviews the experimental setup, experiments, and results of a study by Cañamares and Castells. The original paper focuses on the overarching question of whether popularity is an unwanted bias or a valuable signal in the context of recommender systems. The findings were largely confirmed, but shortcomings in documentation and reproducibility were identified
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either...
The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017Many state-of-the-art ...
Social media inundates us with information about popularity; for example, social media posts are acc...
In this study we conduct a comprehensive set of experiments to evaluate/challenge three graphical ke...
In this reproducibility research of the paper "Should I Follow the Crowd? A Probabilistic Analysis o...
This work is a reproducibility study of the paper "Revisiting Popularity and Demographic Biases in R...
Popularity is often included in experimental evaluation to provide a reference performance for a rec...
Recommender systems help people find relevant content in a personalized way. One main promise of suc...
This report is a reproducibility study of the work of D. Kowald et al. regarding thepopularity bias ...
Numerous recommendation approaches are in use today. However, comparing their effectiveness is a cha...
In this Reproducibility Study of the paper “The Unfairness of Popularity Bias in Music Recommendatio...
The goal of our study is the examination of the reproducibility of the paper The unfairness of popul...
Recommender systems learn from historical users’ feedback that is often non-uniformly distributed ac...
In this paper, we present the results of an empirical evaluation investigating how recommendation a...
In response to the quantity of information available on the Internet, many online service providers ...
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either...
The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017Many state-of-the-art ...
Social media inundates us with information about popularity; for example, social media posts are acc...
In this study we conduct a comprehensive set of experiments to evaluate/challenge three graphical ke...
In this reproducibility research of the paper "Should I Follow the Crowd? A Probabilistic Analysis o...
This work is a reproducibility study of the paper "Revisiting Popularity and Demographic Biases in R...
Popularity is often included in experimental evaluation to provide a reference performance for a rec...
Recommender systems help people find relevant content in a personalized way. One main promise of suc...
This report is a reproducibility study of the work of D. Kowald et al. regarding thepopularity bias ...
Numerous recommendation approaches are in use today. However, comparing their effectiveness is a cha...
In this Reproducibility Study of the paper “The Unfairness of Popularity Bias in Music Recommendatio...
The goal of our study is the examination of the reproducibility of the paper The unfairness of popul...
Recommender systems learn from historical users’ feedback that is often non-uniformly distributed ac...
In this paper, we present the results of an empirical evaluation investigating how recommendation a...
In response to the quantity of information available on the Internet, many online service providers ...
Recommender system evaluation usually focuses on the overall effectiveness of the algorithms, either...
The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017Many state-of-the-art ...
Social media inundates us with information about popularity; for example, social media posts are acc...