论文标题
基于顺序/会话的建议：挑战，方法，应用和机会
Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities
论文作者
论文摘要
近年来，顺序推荐系统（SRSS）和基于会话的推荐系统（SBRS）已成为RSS的新范式，以捕获用户的短期但动态偏好，以实现更及时，更准确的建议。尽管已经对SRS和SBRS进行了广泛的研究，但由于各种描述，设置，假设和应用程序域而引起的该领域有许多不一致之处。没有工作来提供统一的框架和问题声明，以删除SR/SBR领域中常见和各种不一致之处。缺乏工作来提供有关数据特征，关键挑战，大多数代表性和最先进的方法，典型的现实世界应用以及该地区重要的未来研究方向的全面和系统的证明。这项工作旨在填补这些空白，以促进这个令人兴奋且充满活力的地区的进一步研究。
In recent years, sequential recommender systems (SRSs) and session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs to capture users' short-term but dynamic preferences for enabling more timely and accurate recommendations. Although SRSs and SBRSs have been extensively studied, there are many inconsistencies in this area caused by the diverse descriptions, settings, assumptions and application domains. There is no work to provide a unified framework and problem statement to remove the commonly existing and various inconsistencies in the area of SR/SBR. There is a lack of work to provide a comprehensive and systematic demonstration of the data characteristics, key challenges, most representative and state-of-the-art approaches, typical real-world applications and important future research directions in the area. This work aims to fill in these gaps so as to facilitate further research in this exciting and vibrant area.
