The influence of knowledgeable explanations on users' perception of a recommender system

Recommender Systems (RS) help online customers in identifying those items from a variety of choices that best match their presumed needs and preferences. In this context explanations summarize the reasons why a specific item is proposed and are capable of increasing the users' trust in the system's results. This paper presents results from an online experiment on a real-world platform indicating that explanations are an essential piece of functionality of a recommendation system, that significantly increases users' perception of the utility of a recommender system, the intention to use it repeatedly as well as the commitment to recommend it to others.

[1]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[2]  Nava Tintarev,et al.  Explanations of recommendations , 2007, RecSys '07.

[3]  Kyung Hyan Yoo,et al.  Persuasive Recommender Systems - Conceptual Background and Implications , 2012, Springer Briefs in Electrical and Computer Engineering.

[4]  Li Chen,et al.  A user-centric evaluation framework for recommender systems , 2011, RecSys '11.

[5]  Ulrike Bauernfeind,et al.  The Perception of Exploratory Browsing and Trust With Recommender Websites , 2006, J. Inf. Technol. Tour..

[6]  John Riedl,et al.  Explaining collaborative filtering recommendations , 2000, CSCW '00.

[7]  Li Chen,et al.  Trust-inspiring explanation interfaces for recommender systems , 2007, Knowl. Based Syst..

[8]  Dietmar Jannach,et al.  Constraint-Based Recommendation in Tourism: A Multiperspective Case Study , 2009, J. Inf. Technol. Tour..

[9]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[10]  Lior Rokach,et al.  Recommender Systems Handbook , 2010 .

[11]  Gerhard Friedrich,et al.  A Taxonomy for Generating Explanations in Recommender Systems , 2011, AI Mag..

[12]  Gerhard Friedrich,et al.  Recommender Systems - An Introduction , 2010 .

[13]  Markus Zanker,et al.  Knowledgeable Explanations for Recommender Systems , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[14]  Ewald A. Kaluscha,et al.  Empirical research in on-line trust: a review and critical assessment , 2003, Int. J. Hum. Comput. Stud..

[15]  이훈,et al.  지각된 유용성(Perceived Usefulness)의 영향분석 , 2004 .

[16]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[17]  B. Thomas,et al.  Usability Evaluation In Industry , 1996 .

[18]  Judith Masthoff,et al.  Designing and Evaluating Explanations for Recommender Systems , 2011, Recommender Systems Handbook.