31 citations · 53 across the 9 of their papers we have counts for
9 papers
OpenTable data with multi-criteria ratings
Yong Zheng
With the development of recommender systems (RSs), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. Multi-criteria recommender sys…
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open Challenges
Lemei Zhang, Peng Liu, Yashar Deldjoo +2
The emergence of Large Language Models (LLMs) has achieved tremendous success in the field of Natural Language Processing owing to diverse training paradigms that empower LLMs to e…
Hybrid Multi-Criteria Preference Ranking by Subsorting
Yong Zheng, David Xuejun Wang
Multi-criteria recommender systems can improve the quality of recommendations by considering user preferences on multiple criteria. One promising approach proposed recently is mult…
ITM-Rec: An Open Data Set for Educational Recommender Systems
Yong Zheng
With the development of recommender systems (RS), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. However, the education domain m…
Multi-Objective Recommendations: A Tutorial
Yong Zheng, David, Wang
Recommender systems (RecSys) have been well developed to assist user decision making. Traditional RecSys usually optimize a single objective (e.g., rating prediction errors or rank…
Time-Aware Music Recommender Systems: Modeling the Evolution of Implicit User Preferences and User Listening Habits in A Collaborative Filtering Approach
Diego Sánchez-Moreno, Yong Zheng, María N. Moreno-García
Online streaming services have become the most popular way of listening to music. The majority of these services are endowed with recommendation mechanisms that help users to disco…
Interpreting Contextual Effects By Contextual Modeling In Recommender Systems
Yong Zheng
Recommender systems have been widely applied to assist user's decision making by providing a list of personalized item recommendations. Context-aware recommender systems (CARS) add…
Multi-Stakeholder Recommendation: Applications and Challenges
Yong Zheng
Recommender systems have been successfully applied to assist decision making by producing a list of item recommendations tailored to user preferences. Traditional recommender syste…
A User's Guide to CARSKit
Yong Zheng
Context-aware recommender systems extend traditional recommenders by adapting their suggestions to users' contextual situations. CARSKit is a Java-based open-source library specifi…