In emotion-aware music recommender systems, the user’s current emotion is identified and considered in recommending music to him. We have two motivations to extend the existing systems: (1) to the best of our knowledge, the current systems first estimate the user’s emotions and then suggest music based on it. Therefore, the emotion estimation error affects the recommendation accuracy. (2) Studies show that the pattern of users’ interactions with input devices can reflect their emotions. However, these patterns have not been used yet in emotion-aware music recommender systems. In this study, a music recommender system is proposed to suggest music based on users’ keystrokes and mouse clicks patterns. Unlike the previous ones, the proposed system maps these patterns directly to the user’s favorite music, without labeling its current emotion. The results show that even though this system does not use any additional device, it is highly accurate compared to previous methods.

在情绪感知音乐推荐器系统中，在向用户推荐音乐时识别并考虑用户的当前情绪。我们有两种动机来扩展现有的系统：（1）据我们所知，当前的系统首先估计用户的情绪，然后根据其建议音乐。因此，情绪估计误差影响推荐准确性。（2）研究表明，用户与输入设备交互的方式可以反映他们的情绪。但是，这些模式尚未在可感知情感的音乐推荐器系统中使用。在这项研究中，提出了一种音乐推荐器系统，用于根据用户的击键和鼠标点击模式来推荐音乐。与以前的音乐不同，拟议的系统将这些模式直接映射到用户喜欢的音乐，而无需标注其当前情感。