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Humanized Recommender Systems: State-of-the-art and Research Issues
ACM Transactions on Interactive Intelligent Systems ( IF 3.6 ) Pub Date : 2021-07-21 , DOI: 10.1145/3446906
Thi Ngoc Trang Tran 1 , Alexander Felfernig 1 , Nava Tintarev 2
Affiliation  

Psychological factors such as personality, emotions, social connections , and decision biases can significantly affect the outcome of a decision process. These factors are also prevalent in the existing literature related to the inclusion of psychological aspects in recommender system development. Personality and emotions of users have strong connections with their interests and decision-making behavior. Hence, integrating these factors into recommender systems can help to better predict users’ item preferences and increase the satisfaction with recommended items. In scenarios where decisions are made by groups (e.g., selecting a tourism destination to visit with friends), group composition and social connections among group members can affect the outcome of a group decision. Decision biases often occur in a recommendation process, since users usually apply heuristics when making a decision. These biases can result in low-quality decisions. In this article, we provide a rigorous review of existing research on the influence of the mentioned psychological factors on recommender systems. These factors are not only considered in single-user recommendation scenarios but, importantly, also in group recommendation ones, where groups of users are involved in a decision-making process. We include working examples to provide a deeper understanding of how to take into account these factors in recommendation processes. The provided examples go beyond single-user recommendation scenarios by also considering specific aspects of group recommendation settings.

中文翻译:

人性化推荐系统:最新技术和研究问题

心理因素如个性、情感、社会关系, 和决策偏差可以显着影响决策过程的结果。这些因素在现有文献中也普遍存在,这些文献涉及将心理方面纳入推荐系统开发。性格情绪的用户与他们的兴趣和决策行为有很强的联系。因此,将这些因素整合到推荐系统中可以帮助更好地预测用户的项目偏好并提高对推荐项目的满意度。在由团体做出决定的场景中(例如,选择与朋友一起游览的旅游目的地),团体组成社会关系群体成员之间的关系会影响群体决策的结果。决策偏差经常发生在推荐过程中,因为用户在做出决定时通常会应用启发式方法。这些偏差会导致低质量的决策。在本文中,我们对现有关于上述心理因素对推荐系统的影响的研究进行了严格的回顾。这些因素不仅在单用户推荐场景中被考虑,而且重要的是,在群体推荐场景中也被考虑,其中用户组参与决策过程。我们包括工作示例,以更深入地了解如何在推荐过程中考虑这些因素。提供的示例还考虑了组推荐设置的特定方面,超越了单用户推荐场景。
更新日期:2021-07-21
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