A classification-based review recommender

被引：67
|
作者：
O'Mahony, M. P. [1 ]
Smyth, B. [1 ]
机构：
[1] Univ Coll Dublin, CLARITY Ctr Sensor Web Technol, Sch Comp Sci & Informat, Dublin 4, Ireland
来源：
KNOWLEDGE-BASED SYSTEMS | 2010年 / 23卷 / 04期
基金：
爱尔兰科学基金会;
关键词：
User-generated reviews; Classification; Helpful; TripAdvisor;
D O I：
10.1016/j.knosys.2009.11.004
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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
引用
收藏
页码：323 / 329
页数：7
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