d202210648@xs.ustb.edu.cn
Author
Contributions by role
Author 1
Yiquan An
University of Science and Technology Beijing
Summary
Yiquan An received his BS and MS degrees in College of Economics and Management, Taiyuan University of Technology, China, in 2018 and 2022, respectively. He is currently a PhD candidate in University of Science and Technology Beijing. His current research interests include deep transfer learning, causal structure discovery, and industrial data mining and modeling.
Edited Journals
IECE Contributions

Free Access | Review Article | 15 October 2024
Recommender System: A Comprehensive Overview of Technical Challenges and Social Implications
IECE Transactions on Sensing, Communication, and Control | Volume 1, Issue 1: 30-51, 2024 | DOI:10.62762/TSCC.2024.898503
Abstract
The proliferation of Recommender Systems (RecSys), driven by their expanding application domains, explosive data growth, and exponential advancements in computing capabilities, has cultivated a dynamic and evolving research landscape. This paper comprehensively reviews the foundational concepts, methodologies, and challenges associated with RecSys from technological and social scientific lenses. Initially, it categorizes personalized RecSys technical solutions into five paradigms: collaborative filtering, scenario-aware, knowledge & data co-driven approaches, large language models, and hybrid models integrating diverse data sources. Subsequently, the paper analyses the key challenges and fut... More >

Graphical Abstract
Recommender System: A Comprehensive Overview of Technical Challenges and Social Implications