State of art and emerging trends on group recommender system: a comprehensive review
A group recommender system (GRS) generates suggestions for a group of individuals,
considering not only each person's preferences but also factors such as social dynamics …
considering not only each person's preferences but also factors such as social dynamics …
Our Model Achieves Excellent Performance on MovieLens: What Does it Mean?
A typical benchmark dataset for recommender system (RecSys) evaluation consists of user-
item interactions generated on a platform within a time period. The interaction generation …
item interactions generated on a platform within a time period. The interaction generation …
A survey on fairness of large language models in e-commerce: progress, application, and challenge
This survey explores the fairness of large language models (LLMs) in e-commerce,
examining their progress, applications, and the challenges they face. LLMs have become …
examining their progress, applications, and the challenges they face. LLMs have become …
Mitigating Exposure Bias in Recommender Systems–A Comparative Analysis of Discrete Choice Models
When implicit feedback recommender systems expose users to items, they influence the
users' choices and, consequently, their own future recommendations. This effect is known as …
users' choices and, consequently, their own future recommendations. This effect is known as …
Popularity Bias in Correlation Graph based API Recommendation for Mashup Creation
The explosive growth of the API economy in recent years has led to a dramatic increase in
available APIs. Mashup development, a dominant approach for creating data-centric …
available APIs. Mashup development, a dominant approach for creating data-centric …
A Survey on Intent-aware Recommender Systems
Many modern online services feature personalized recommendations. A central challenge
when providing such recommendations is that the reason why an individual user accesses …
when providing such recommendations is that the reason why an individual user accesses …
Beyond Collaborative Filtering: A Relook at Task Formulation in Recommender Systems
A Sun - ACM SIGWEB Newsletter, 2024 - dl.acm.org
Recommender Systems (RecSys) have become indispensable in numerous applications,
profoundly influencing our everyday experiences. Despite their practical significance …
profoundly influencing our everyday experiences. Despite their practical significance …
The Fault in Our Recommendations: On the Perils of Optimizing the Measurable
Recommendation systems are widespread, and through customized recommendations,
promise to match users with options they will like. To that end, data on engagement is …
promise to match users with options they will like. To that end, data on engagement is …
Transparency, Privacy, and Fairness in Recommender Systems
D Kowald - arXiv preprint arXiv:2406.11323, 2024 - arxiv.org
Recommender systems have become a pervasive part of our daily online experience, and
are one of the most widely used applications of artificial intelligence and machine learning …
are one of the most widely used applications of artificial intelligence and machine learning …
" Global is Good, Local is Bad?": Understanding Brand Bias in LLMs
M Kamruzzaman, HM Nguyen, GL Kim - arXiv preprint arXiv:2406.13997, 2024 - arxiv.org
Many recent studies have investigated social biases in LLMs but brand bias has received
little attention. This research examines the biases exhibited by LLMs towards different …
little attention. This research examines the biases exhibited by LLMs towards different …