Authors : Chuhan Wu , Fangzhao Wu , Yongfeng Huang , Xing Xie Authors Info & Claims
Article No.: 24, Pages 1 - 50 Published : 10 January 2023 Publication History 55 citation 3,932 Downloads Total Citations 55 Total Downloads 3,932 Last 12 Months 1,833 Last 6 weeks 138 Get Citation AlertsThis alert has been successfully added and will be sent to: You will be notified whenever a record that you have chosen has been cited.
To manage your alert preferences, click on the button below. Manage my AlertsPersonalized news recommendation is important for users to find interesting news information and alleviate information overload. Although it has been extensively studied over decades and has achieved notable success in improving user experience, there are still many problems and challenges that need to be further studied. To help researchers master the advances in personalized news recommendation, in this article, we present a comprehensive overview of personalized news recommendation. Instead of following the conventional taxonomy of news recommendation methods, in this article, we propose a novel perspective to understand personalized news recommendation based on its core problems and the associated techniques and challenges. We first review the techniques for tackling each core problem in a personalized news recommender system and the challenges they face. Next, we introduce the public datasets and evaluation methods for personalized news recommendation. We then discuss the key points on improving the responsibility of personalized news recommender systems. Finally, we raise several research directions that are worth investigating in the future. This article can provide up-to-date and comprehensive views on personalized news recommendation. We hope this article can facilitate research on personalized news recommendation as well as related fields in natural language processing and data mining.
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