With the emergence of personality computing as a new research field related to artificial intelligence and personality psychology, we have witnessed an unprecedented proliferation of personality-aware recommendation systems. Unlike conventional recommendation systems, these new systems solve traditional problems such as the cold start and data sparsity problems. This survey aims to study and systematically classify personality-aware recommendation systems. To the best of our knowledge, this survey is the first that focuses on personality-aware recommendation systems. We explore the different design choices of personality-aware recommendation systems, by comparing their personality modeling methods, as well as their recommendation techniques. Furthermore, we present the commonly used datasets and point out some of the challenges of personality-aware recommendation systems.

中文翻译：

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个性意识推荐系统调查

随着个性计算作为与人工智能和个性心理学相关的新研究领域的兴起，我们见证了个性感知推荐系统的空前增长。与常规推荐系统不同，这些新系统解决了诸如冷启动和数据稀疏性问题之类的传统问题。这项调查旨在研究个性识别系统并对其进行系统分类。据我们所知，本次调查是第一个侧重于个性感知推荐系统的调查。通过比较个性感知推荐系统的个性化建模方法和推荐技术，我们探索了个性感知推荐系统的不同设计选择。此外，