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Opinionated explanations for recommendation systems

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
This paper describes a novel approach for generating explanations for recommender systems based on opinions in user-generated reviews. We show how these opinions can be used to construct helpful and compelling explanations at recommendation time. The explanation highlights how the pros and cons of a recommended item compares to alternative items. We propose a way to score these explanations based on their content. The scores help to identify compelling explanations, providing a strong reason why the item being explained is better or worse than the alternatives. We describe the results of offline experiments and a live-user study based on TripAdvisor data to demonstrate the usefulness of this approach.
Digital Object Identifer (DOI): 
10.1007/978-3-319-25032-8_25
Publication Date: 
01/01/2015
Research Group: 
Institution: 
National University of Ireland, Dublin (UCD)
Open access repository: 
No