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Emotive and personality parameters in recommender systems: Recognition and usage of user-centric data for user and item modeling in content retrieval systems - Softcover
Inhaltsangabe
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.
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Reseña del editor
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.
Biografía del autor
Marko Tkal?i? (right), PhD, researcher at the University of Ljubljana (UL), research interests cover the role of emotions in human computer interactions. Andrej Ko?ir (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.
Marko Tkal?i? (right), PhD, researcher at the University of Ljubljana (UL), research interests cover the role of emotions in human computer interactions. Andrej Ko?ir (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.
Marko Tkal?i? (right), PhD, researcher at the University of Ljubljana (UL), research interests cover the role of emotions in human computer interactions. Andrej Ko?ir (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.
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Emotive and personality parameters in recommender systems
Verlag:
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844333096
ISBN 13: 9783844333091
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
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Zustand: New. Artikel-Nr. 5473681
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Foto des Verkäufers
Emotive and personality parameters in recommender systems
Verlag:
LAP LAMBERT Academic Publishing Apr 2011, 2011
ISBN 10: 3844333096
ISBN 13: 9783844333091
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 104 pp. Englisch. Artikel-Nr. 9783844333091
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