基于深度学习的情境感知推荐系统研究进展

传统的推荐系统存在数据高度稀疏、冷启动及用户偏好建模难等问题,而把情境信息融入推荐系统中能有效缓解此类问题.深度学习技术已经成为人工智能领域研究热点,把深度学习应用在情境感知推荐系统当中,为推荐领域的研究带来新的机遇与挑战.本文从情境感知推荐系统相关概念出发,综合整理国内外研究相关文献,介绍深度学习技术融入情境感知推荐系统相关应用模型,提出了基于深度学习的情境感知推荐系统研究的不足以及对未来的展望.

Review on Deep Learning Based Context-Aware Recommender Systems

Integrating context information into the traditional recommendation systems can effectively solve the problems such as data highly sparse, cold boot, and difficult to model user preference. Deep learning technology has become a research hotspot in the field of artificial intelligence in recent years, it will bring new opportunities and challenges to research in the field of recommendation while deep learning is applied into context-aware recommender systems. In this paper, some application models about the integration of deep learning technology into context-aware recommendation systems are mentioned, and deficiency of context-aware recommender systems based on deep learning and prospect in the future are elaborated at the same time, by introducing the related concepts of context-aware recommender systems and collating relevant research literatures worldwide.