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Opinionated Product Recommendation


Ruihai Dong, Markus Schaal, Michael P O'Mahony, Kevin McCarthy, Barry Smyth

Publication Type: 
Refereed Conference Meeting Proceeding
In this paper we describe a novel approach to case-based product recommendation. It is novel because it does not leverage the usual static, feature-based, purely similarity-driven approaches of tradi- tional case-based recommenders. Instead we harness experiential cases, which are automatically mined from user generated reviews, and we use these as the basis for a form of recommendation that emphasises simi- larity and sentiment. We test our approach in a realistic product recom- mendation setting by using live-product data and user reviews
Conference Name: 
ICCBR 2013
Digital Object Identifer (DOI): 
Publication Date: 
Conference Location: 
United States of America
Research Group: 
National University of Ireland, Dublin (UCD)
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