Learning to recommend helpful hotel reviews

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Title: Learning to recommend helpful hotel reviews
Authors: O'Mahony, Michael P.
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/1894
Date: Oct-2009
Abstract: User-generated reviews are a common and valuable source of product information, yet little attention has been paid as to how best to present them to end-users. In this paper, we describe a classification-based recommender system that is designed to recommend the most helpful reviews for a given product. We present a large-scale evaluation of our approach using TripAdvisor hotel reviews, and we show that our approach is capable of suggesting superior reviews compared to a number of alternative recommendation benchmarks.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2009 ACM
Keywords: Review RecommendationClassificationTripAdvisor
Subject LCSH: Recommender systems (Information filtering)
Automatic classification
User-generated content--Classification
DOI: 10.1145/1639714.1639774
Other versions: http://doi.acm.org/10.1145/1639714.1639774
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings of the third ACM conference on Recommender systems
Conference Details: Paper presented at the 3rd ACM Conference on Recommender Systems (RecSys 2009), New York City, NY, USA, 22-25 October 2009
ISBN: 978-1-60558-435-5
metadata.dc.date.available: 2010-03-29T15:43:20Z
Appears in Collections:CLARITY Research Collection
Computer Science Research Collection

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