Recent Developments in Recommender Systems: A Survey [Review Article]
推荐系统
计算机科学
数据科学
情报检索
作者
Yang Li,Kangbo Liu,Ranjan Satapathy,Suhang Wang,Erik Cambria
出处
期刊:IEEE Computational Intelligence Magazine [Institute of Electrical and Electronics Engineers] 日期:2024-04-08卷期号:19 (2): 78-95被引量:14
标识
DOI:10.1109/mci.2024.3363984
摘要
In this technical survey, the latest advancements in the field of recommender systems are comprehensively summarized. The objective of this study is to provide an overview of the current state-of-the-art in the field and highlight the latest trends in the development of recommender systems. It starts with a comprehensive summary of the main taxonomy of recommender systems, including personalized and group recommender systems. In addition, the survey analyzes the robustness, data bias, and fairness issues in recommender systems, summarizing the evaluation metrics used to assess the performance of these systems. Finally, it provides insights into the latest trends in the development of recommender systems and highlights the new directions for future research in the field.