Tourism E-Commerce Recommender System Based on Web Data Mining

被引：0
|
作者：
Zhao, Xuesong [1 ]
Ji, Kaifan [2 ]
机构：
[1] Kunming Univ Sci & Technol, Oxbridge Coll, Kunming, Peoples R China
[2] Kunming Univ Sci & Technol, Comp Technol Applicat Key Lab, Kunming, Peoples R China
来源：
PROCEEDINGS OF THE 2013 8TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2013) | 2013年
关键词：
recommender system; web data mining; tourism e-commerce;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Recommender system based on web data mining is widely used in e-commerce for it generates more accurate and objective recommendation results and provides personalized service for web users. This paper makes analysis on some major recommendation methods based on web data mining such as Collaborative Filtering and Association Rules mining, and discusses the practical application of these methods in the tourism e-commerce, and then presents a design of web mining based tourism e-commerce recommender system with offline and online modules.
引用
收藏
页码：1485 / 1488
页数：4
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