Abstract
Personalized systems traditionally used the traces of user interactions to learn the user model, which was used by sophisticated algorithms to choose the appropriate content for the user and the situation. Recently, new types of user models started to emerge, which take into account more user-centric information, such as emotions and personality. Initially, these models were conceptually interesting but of little practical value as emotions and personality were difficult to acquire. However, with the recent advancement in unobtrusive technologies for the detection of emotions and personality these models are becoming interesting both for researchers and practitioners in the domain of personalized systems. This chapter introduces the book, which aims at covering the whole spectrum of knowledge needed to research and develop emotion- and personality-aware systems. The chapters cover (i) psychological theories, (ii) computational methods for the unobtrusive acquisition of emotions and personality, (iii) applications of personalized systems in recommender systems, conversational systems, music information retrieval, and e-learning, (iv) evaluation methods, and (v) privacy issues.