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- W2115613989 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." @default.
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- W2115613989 date "2009-10-23" @default.
- W2115613989 modified "2023-10-07" @default.
- W2115613989 title "Learning to recommend helpful hotel reviews" @default.
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- W2115613989 doi "https://doi.org/10.1145/1639714.1639774" @default.
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