386 citations · 828 across the 18 of their papers we have counts for
24 papers · 1 filter
Leveraging Large Language Models for Sequential Recommendation
Jesse Harte, Wouter Zorgdrager, Panos Louridas +3
Sequential recommendation problems have received increasing attention in research during the past few years, leading to the inception of a large variety of algorithmic approaches.…
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems
Xiaocong Chen, Siyu Wang, Julian McAuley +2
Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significa…
Economic Recommender Systems -- A Systematic Review
Alvise De Biasio, Nicolò Navarin, Dietmar Jannach
Many of today's online services provide personalized recommendations to their users. Such recommendations are typically designed to serve certain user needs, e.g., to quickly find…
A Survey on Point-of-Interest Recommendations Leveraging Heterogeneous Data
Zehui Wang, Wolfram Höpken, Dietmar Jannach
Tourism is an important application domain for recommender systems. In this domain, recommender systems are for example tasked with providing personalized recommendations for trans…
A Survey on Popularity Bias in Recommender Systems
Anastasiia Klimashevskaia, Dietmar Jannach, Mehdi Elahi +1
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…
Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning
Siyu Wang, Xiaocong Chen, Dietmar Jannach +1
Reinforcement learning-based recommender systems have recently gained popularity. However, the design of the reward function, on which the agent relies to optimize its recommendati…