Fairness in recommender systems: research landscape and future directions
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
A survey on popularity bias in recommender systems
Recommender systems help people find relevant content in a personalized way. One main
promise of such systems is that they are able to increase the visibility of items in the long tail …
promise of such systems is that they are able to increase the visibility of items in the long tail …
Cpfair: Personalized consumer and producer fairness re-ranking for recommender systems
Recently, there has been a rising awareness that when machine learning (ML) algorithms
are used to automate choices, they may treat/affect individuals unfairly, with legal, ethical, or …
are used to automate choices, they may treat/affect individuals unfairly, with legal, ethical, or …
A novel time-aware food recommender-system based on deep learning and graph clustering
Food recommender-systems are considered an effective tool to help users adjust their
eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food …
eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food …
Understanding biases in chatgpt-based recommender systems: Provider fairness, temporal stability, and recency
Y Deldjoo - ACM Transactions on Recommender Systems, 2024 - dl.acm.org
This paper explores the biases inherent in ChatGPT-based recommender systems, focusing
on provider fairness (item-side fairness). Through extensive experiments and over a …
on provider fairness (item-side fairness). Through extensive experiments and over a …
[HTML][HTML] A unifying and general account of fairness measurement in recommender systems
Fairness is fundamental to all information access systems, including recommender systems.
However, the landscape of fairness definition and measurement is quite scattered with many …
However, the landscape of fairness definition and measurement is quite scattered with many …
[HTML][HTML] A novel healthy and time-aware food recommender system using attributed community detection
Food recommendation systems aim to provide recommendations according to a user's diet,
recipes, and preferences. These systems are deemed useful for assisting users in changing …
recipes, and preferences. These systems are deemed useful for assisting users in changing …
Multimedia recommender systems: Algorithms and challenges
This chapter studies state-of-the-art research related to multimedia recommender systems
(MMRS), focusing on methods that integrate multimedia content as side information to …
(MMRS), focusing on methods that integrate multimedia content as side information to …
[HTML][HTML] The role of context fusion on accuracy, beyond-accuracy, and fairness of point-of-interest recommendation systems
Abstract Point-of-interest (POI) recommendation is an essential service to location-based
social networks (LBSNs), benefiting both users providing them the chance to explore new …
social networks (LBSNs), benefiting both users providing them the chance to explore new …
Content-driven music recommendation: Evolution, state of the art, and challenges
The music domain is among the most important ones for adopting recommender systems
technology. In contrast to most other recommendation domains, which predominantly rely on …
technology. In contrast to most other recommendation domains, which predominantly rely on …