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A classification-based review recommender
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DOI：10.1016/j.knosys.2009.11.004.png)
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摘要
En 中文
Many online stores encourage their users to submit product or service reviews in order to guide future purchasing decisions These reviews are often listed alongside product recommendations but, to date, limited attention has been paid as to how best to present these reviews to the end-user In this paper, we describe a supervised classification approach that is designed to Identify and recommend the most helpful product reviews Using the TripAdvisor service as a case study, we compare the performance of several classification techniques using a range of features derived from hotel reviews We then describe how these classifiers can be used as the basis for a practical recommender that automatically suggests the most-helpful contrasting reviews to end-users We present an empirical evaluation which shows that our approach achieves a statistically significant improvement over alternative review ranking schemes (C) 2009 Elsevier B V All rights reserved
Keyword:
User-generated reviews
Classification
Helpful
TripAdvisor
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期刊
K
IF:
7.6
论文数:
1.2W
被引数:
4.5W
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