Hybrid Filtering-Based Personalized Recommender System for Revitalization of Jeju Water Industry

被引：0
|
作者：
Cho, Jungwon [1 ]
Kang, Eui-young [1 ]
Kim, Hanil [1 ]
Kim, Hyungchul [1 ]
Lee, Youngseok [2 ]
Jeong, Seungdo [3 ]
机构：
[1] Jeju Natl Univ, Dept Comp Educ, 66 Jeju Daehaklo, Jeju Si 690756, Jeju Do, South Korea
[2] Hanyang Univ, Dept Elect & Comp Engn, Seoul 133791, South Korea
[3] Hanyang Cyber Univ, Dept Informat & Commun Engn, Seoul 133791, South Korea
来源：
NEW HORIZONS IN WEB-BASED LEARNING: ICWL 2010 WORKSHOPS | 2011年 / 6537卷
基金：
新加坡国家研究基金会;
关键词：
Jeju Water Industry; personalization; hybrid filtering; recommender framework; recommender system; tourist recommender; Jeju beer recommender;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Information filtering is one of the core technologies in a recommender system for personalized services. Each filtering technology has such shortcomings as new user problems and sparsity. Moreover, a recommender system dependent on items decreases reusability. In order to solve these problems, we developed a personalized recommender framework with hybrid filtering. This framework consists of reusable and flexible modules for recommended items. Further, this framework improves the productivity of programming. As an application of this framework, we implemented a personalized tourist recommender system and analyzed it. Also, we applied the system to Jeju beer recommender system. The results show the performance of the framework proposed in this paper.
引用
收藏
页码：55 / +
页数：2
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