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 review of modern fashion recommender systems
The textile and apparel industries have grown tremendously over the past few years.
Customers no longer have to visit many stores, stand in long queues, or try on garments in …
Customers no longer have to visit many stores, stand in long queues, or try on garments in …
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 …
Up5: Unbiased foundation model for fairness-aware recommendation
Recent advancements in foundation models such as large language models (LLM) have
propelled them to the forefront of recommender systems (RS). Moreover, fairness in RS is …
propelled them to the forefront of recommender systems (RS). Moreover, fairness in RS is …
Siamese neural networks in recommendation
N Serrano, A Bellogín - Neural Computing and Applications, 2023 - Springer
Recommender systems are widely adopted as an increasing research and development
area, since they provide users with diverse and useful information tailored to their needs …
area, since they provide users with diverse and useful information tailored to their needs …
[HTML][HTML] Health-aware food recommendation system with dual attention in heterogeneous graphs
Recommender systems (RS) have been increasingly applied to food and health. However,
challenges still remain, including the effective incorporation of heterogeneous information …
challenges still remain, including the effective incorporation of heterogeneous information …
Fairness of ChatGPT and the role of explainable-guided prompts
Y Deldjoo - Joint European Conference on Machine Learning and …, 2023 - Springer
Our research investigates the potential of Large-scale Language Models (LLMs), specifically
OpenAI's GPT, in credit risk assessment-a binary classification task. Our findings suggest …
OpenAI's GPT, in credit risk assessment-a binary classification task. Our findings suggest …
Average User-Side Counterfactual Fairness for Collaborative Filtering
Recently, the user-side fairness issue in Collaborative Filtering (CF) algorithms has gained
considerable attention, arguing that results should not discriminate an individual or a sub …
considerable attention, arguing that results should not discriminate an individual or a sub …
Towards fair and personalized federated recommendation
Recommender systems have gained immense popularity in recent years for predicting
users' interests by learning embeddings. The majority of existing recommendation …
users' interests by learning embeddings. The majority of existing recommendation …
[HTML][HTML] Debiaser for Multiple Variables to enhance fairness in classification tasks
Nowadays assuring that search and recommendation systems are fair and do not apply
discrimination among any kind of population has become of paramount importance. This is …
discrimination among any kind of population has become of paramount importance. This is …