The growing amount of multimedia content is making it hard for end users to find the relevant content. The goal of recommender systems is to assist the users by finding a small subset of relevant multimedia items for each user. State-of-the-art techniques for recommending content are very data-centric. The progress beyond the state-of-the-art presented in this book consists in introducing new parameters based on emotions and personality that explain a substantial part of variance in the end users' preferences. The book covers the detection of emotions and personality factors of end users. The...