Emotive and personality parameters in recommender systems - Tkalcic, Marko;Kosir, Andrej;Tasic, Jurij F.
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  • Broschiertes Buch

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…mehr

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Produktbeschreibung
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 book then shows clearly how to use these user-centric data to model end users and thus improve the performance of a recommender system for images. The book will serve as a guideline and inspiration for practitioners and academics in content retrieval and affecting computing.
Autorenporträt
Marko Tkal¿i¿ (right), PhD, researcher at the University of Ljubljana (UL), research interests cover the role of emotions in human computer interactions. Andrej Köir (left), PhD, professor at UL, research areas include operational research and user personalization. Jurij Tasi¿ (middle), PhD, professor of system theory and computing at UL.