A Consumer Review-Driven Recommender Service for Web E-Commerce

被引：15
|
作者：
Lin, Keng-Pei [1 ]
Shen, Chih-Ya [2 ]
Chang, Tzu-Lin [3 ]
Chang, Te-Min [1 ]
机构：
[1] Natl Sun Yat Sen Univ, Dept Informat Management, Kaohsiung, Taiwan
[2] Natl Tsing Hua Univ, Dept Comp Sci, Hsinchu, Taiwan
[3] Natl Taiwan Univ, Dept Accounting, Taipei, Taiwan
来源：
2017 IEEE 10TH CONFERENCE ON SERVICE-ORIENTED COMPUTING AND APPLICATIONS (SOCA) | 2017年
关键词：
recommender systems; e-commerce; topic modeling;
D O I：
10.1109/SOCA.2017.35
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Consumer reviews play an important role in various e-commerce sites like hotel reservation and app stores. Online consumer reviews are informative because they convey consumers' actual experiences and evaluations to the products and services they received. In this paper, we leverage the consumer reviews to develop a review-driven recommender service for e-commerce websites. We semantically explore the topics in reviews to derive the product features and infer the preferences of consumers for making recommendations. We conduct large-scale experiments on real-world data. The results manifest that the proposed recommender service is effective for web e-commerce.
引用
收藏
页码：206 / 210
页数：5
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