Recommender Systems supporting Decision Making through Analysis of User Emotions and Personality

8 years 7 days ago

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The inﬂuence of emotions in decision making is a popular research topic in psychology and cognitive studies. A person facing a choosing problem has to consider diﬀerent solutions and take a decision. During this process several elements inﬂuence the reasoning, some of them are rational, others are irrational, such as emotions. Recommender Systems can be used to support decision making by narrowing the space of options. Typically they do not consider irrational elements during the computational process, but recent studies show that accuracy of suggestions improves whether user’s emotional state is included in the recommendation process. In this paper we propose the idea of deﬁning a framework for an Emotion-Aware Recommender System. The user emotions will be formalized in an aﬀective user proﬁle which can act as an emotional computational model. The Recommender System will use the aﬀective proﬁle integrated with case base reasoning to compute recommendations.

Marco Polignano, Marco de Gemmis

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