论文标题
顺序推荐系统：挑战，进步和前景
Sequential Recommender Systems: Challenges, Progress and Prospects
论文作者
论文摘要
近年来，顺序推荐系统的新兴主题引起了人们的关注。与传统的推荐系统不同，包括协作过滤和基于内容的过滤，SRSS试图理解和建模顺序用户行为，用户和项目之间的互动以及用户偏好的演变和项目的越来越广泛。 SRSs involve the above aspects for more precise characterization of user contexts, intent and goals, and item consumption trend, leading to more accurate, customized and dynamic recommendations.In this paper, we provide a systematic review on SRSs.We first present the characteristics of SRSs, and then summarize and categorize the key challenges in this research area, followed by the corresponding research progress consisting of the most recent and representative developments on this topic.Finally, we讨论这个充满活力的地区的重要研究方向。
The emerging topic of sequential recommender systems has attracted increasing attention in recent years.Different from the conventional recommender systems including collaborative filtering and content-based filtering, SRSs try to understand and model the sequential user behaviors, the interactions between users and items, and the evolution of users preferences and item popularity over time. SRSs involve the above aspects for more precise characterization of user contexts, intent and goals, and item consumption trend, leading to more accurate, customized and dynamic recommendations.In this paper, we provide a systematic review on SRSs.We first present the characteristics of SRSs, and then summarize and categorize the key challenges in this research area, followed by the corresponding research progress consisting of the most recent and representative developments on this topic.Finally, we discuss the important research directions in this vibrant area.
