A Live-User Study of Opinionated Explanations for Recommender Systems
Refereed Conference Meeting Proceeding
This paper describes an approach for generating rich and compelling explanations in recommender systems, based on opinions mined from user-generated reviews. The explanations highlight the features of a recommended item that matter most to the user and also relate them to other recommendation alternatives and the user‘s past activities to provide a context.
IUI 2016 Conference
Digital Object Identifer (DOI):
United States of America
National University of Ireland, Dublin (UCD)
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