Exploring Reviews and Ratings on Reviews for Personalized Search

被引：1
|
作者：
Yang, Yang [1 ]
Hu, Shuyue [1 ]
Cai, Yi [1 ]
Du, Qing [1 ]
Leung, Ho-fung [2 ]
Lau, Raymond Y. K. [3 ]
机构：
[1] South China Univ Technol, Sch Software Engn, Guangzhou, Guangdong, Peoples R China
[2] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China
[3] City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R China
来源：
CURRENT DEVELOPMENTS IN WEB BASED LEARNING, ICWL 2015 | 2016年 / 9584卷
关键词：
Personalized search; User profiling; Review;
D O I：
10.1007/978-3-319-32865-2_16
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the development of e-commerce, e-commerce websites become very popular. People write reviews on products and rate the helpfulness of reviews in these websites. Reviews written by a user and reviews rated by a user actually reflect a user's interests and disinterest. Thus, they are very useful for user profiling. In this paper, we explore users' reviews and ratings on reviews for personalized search and propose a review-based user profiling method. And we also propose a priority-based result ranking strategy. For evaluation, we conduct experiments on a real-life data set. The experimental results show that our method can significantly improve the retrieval quality.
引用
收藏
页码：140 / 150
页数：11
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