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ABSTRACT
Based on our recent work on the development of a trust model for recommender agents and a qualitative survey, we explore the potential of building users' trust with explanation interfaces. We present the major results from the survey, which provided a roadmap identifying the most promising areas for investigating design issues for trust-inducing interfaces. We then describe a set of general principles derived from an in-depth examination of various design dimensions for constructing explanation interfaces, which most contribute to trust formation. We present results of a significant-scale user study, which indicate that the organization-based explanation is highly effective in building users' trust in the recommendation interface, with the benefit of increasing users' intention to return to the agent and save cognitive effort.
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CITED BY 10
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Simone Stumpf , Vidya Rajaram , Lida Li , Margaret Burnett , Thomas Dietterich , Erin Sullivan , Russell Drummond , Jonathan Herlocker, Toward harnessing user feedback for machine learning, Proceedings of the 12th international conference on Intelligent user interfaces, January 28-31, 2007, Honolulu, Hawaii, USA
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Pengyi Zhang , Lynne Plettenberg , Judith L. Klavans , Douglas W. Oard , Dagobert Soergel, Task-based interaction with an integrated multilingual, multimedia information system: a formative evaluation, Proceedings of the 2007 conference on Digital libraries, June 18-23, 2007, Vancouver, BC, Canada
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Simone Stumpf , Vidya Rajaram , Lida Li , Weng-Keen Wong , Margaret Burnett , Thomas Dietterich , Erin Sullivan , Jonathan Herlocker, Interacting meaningfully with machine learning systems: Three experiments, International Journal of Human-Computer Studies, v.67 n.8, p.639-662, August, 2009
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