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 …
Fairness in deep learning: A survey on vision and language research
Despite being responsible for state-of-the-art results in several computer vision and natural
language processing tasks, neural networks have faced harsh criticism due to some of their …
language processing tasks, neural networks have faced harsh criticism due to some of their …
A survey on the fairness of recommender systems
Recommender systems are an essential tool to relieve the information overload challenge
and play an important role in people's daily lives. Since recommendations involve …
and play an important role in people's daily lives. Since recommendations involve …
Fairness in graph mining: A survey
Graph mining algorithms have been playing a significant role in myriad fields over the years.
However, despite their promising performance on various graph analytical tasks, most of …
However, despite their promising performance on various graph analytical tasks, most of …
Empowering news recommendation with pre-trained language models
Personalized news recommendation is an essential technique for online news services.
News articles usually contain rich textual content, and accurate news modeling is important …
News articles usually contain rich textual content, and accurate news modeling is important …
Fairness in recommendation: A survey
As one of the most pervasive applications of machine learning, recommender systems are
playing an important role on assisting human decision making. The satisfaction of users and …
playing an important role on assisting human decision making. The satisfaction of users and …
[HTML][HTML] A survey on fairness-aware recommender systems
As information filtering services, recommender systems have extremely enriched our daily
life by providing personalized suggestions and facilitating people in decision-making, which …
life by providing personalized suggestions and facilitating people in decision-making, which …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
Joint multisided exposure fairness for recommendation
Prior research on exposure fairness in the context of recommender systems has focused
mostly on disparities in the exposure of individual or groups of items to individual users of …
mostly on disparities in the exposure of individual or groups of items to individual users of …
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 …