A Framework for Emotion-aware Recommender Systems supporting Decision Making

Emotions influence ever yday decisions. When people make decisions about movies to watch, songs to listen or even about more serious issues such as health, they perform a cognitive process that estimates which of various alternative choices would yield the most positive consequences. Indeed, this process in not totally rational because it is influenced, directly or in a subtle way by personality traits and emotions. In this paper we propose the idea of defining an affective user profile , which can act as a computational model of personality and emotions, included in a g eneral, affective-aware , recommendation framework