The daily and routine interactions of people with their smartphones in various situations make these devices valuable data sources to understand user behaviors. Passive users’ emotion recognition is one of the most essential user modeling areas and has been studied for various purposes so far. Psychological studies, on the other hand, show that the personality of users can influence their behavior when they experience different emotions. Individuals with varying types of personality exhibit different reactions in the same emotional situation. It is concluded that if we consider the user’s personality in passive recognition of his/her emotion, the emotion can be identified more accurately. However, researchers have not paid enough attention to the users’ personality traits when identifying the users’ emotions based on their interaction with cell phones. In the present study, we strive to address this research gap. Among the various emotions, our focus is on happiness recognition. In our proposed method, the user’s personality traits are first estimated based on his/her interactions with the smartphone. Then the estimated personality of the user, along with the data of his/her interactions with the smartphone, is taken into account to recognize his/her happiness. Evaluations showed that taking into account the users’ personality traits reduces the happiness recognition error.

人们在各种情况下与智能手机的日常和日常交互使这些设备成为了解用户行为的宝贵数据源。被动用户的情感识别是最重要的用户建模领域之一，到目前为止，已针对各种目的进行了研究。另一方面，心理学研究表明，用户的个性在经历不同的情感时会影响他们的行为。具有不同类型人格的个体在相同的情绪情况下会表现出不同的反应。结论是，如果我们在被动识别用户的情绪时考虑其个性，则可以更准确地识别情绪。然而，研究人员在根据用户与手机的互动来识别用户的情绪时，并未对用户的个性特征给予足够的重视。在本研究中，我们努力解决这一研究空白。在各种情感中，我们的重点是幸福感。在我们提出的方法中，首先基于用户与智能手机的交互来估计用户的个性特征。然后，将估计的用户个性以及他/她与智能手机互动的数据考虑在内，以识别他/她的幸福。评价表明，考虑到用户的个性特征会减少幸福识别错误。首先根据用户与智能手机的互动来估算用户的个性特征。然后，将估计的用户个性以及他/她与智能手机互动的数据考虑在内，以识别他/她的幸福。评价表明，考虑到用户的个性特征会减少幸福识别错误。首先根据用户与智能手机的互动来估算用户的个性特征。然后，将估计的用户个性以及他/她与智能手机互动的数据考虑在内，以识别他/她的幸福。评价表明，考虑到用户的个性特征会减少幸福识别错误。