With the advent of e-commerce applications and the ever growing popularity of social networking tools, a novel kind of recommender systems has been born; the so-called trustenhanced recommenders which infer trust information from the social network between their users, and incorporate this knowledge into the recommendation process to obtain more personalized recommendations. Since the pioneering work of Jennifer Golbeck and Paolo Massa, research on trust-based recommendations is thriving and attracts and inspires an increasing number of scientists around the world. In this book, we contributed to some of the most recent and exciting developments in this still nascent domain, namely the potential of distrust, recommendations for controversial items, and connection guidance for cold start users.
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