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- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)
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About this book
Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.
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Table of contents (8 chapters)
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Bibliographic Information
Book Title: Persuasive Recommender Systems
Book Subtitle: Conceptual Background and Implications
Authors: Kyung-Hyan Yoo, Ulrike Gretzel, Markus Zanker
Series Title: SpringerBriefs in Electrical and Computer Engineering
DOI: https://doi.org/10.1007/978-1-4614-4702-3
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-1-4614-4701-6Published: 17 August 2012
eBook ISBN: 978-1-4614-4702-3Published: 17 August 2012
Series ISSN: 2191-8112
Series E-ISSN: 2191-8120
Edition Number: 1
Number of Pages: VI, 59
Number of Illustrations: 9 b/w illustrations
Topics: Artificial Intelligence, Data Mining and Knowledge Discovery