Name
Title | ||
|---|---|---|
Hybrid filtering-based personalized recommender system for revitalization of Jeju water industry |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-20539-2_7 | ICWL Workshops |
Keywords | Field | DocType |
new user problem,personalized service,recommender system,recommended item,jeju beer recommender system,personalized tourist recommender system,flexible module,hybrid filtering-based personalized recommender,personalized recommender framework,core technology,jeju water industry,personalization | Recommender system,World Wide Web,Computer science,Filter (signal processing),Water industry,Multimedia,Reusability,Personalization | Conference |
Volume | ISSN | Citations |
6537 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 6 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jungwon Cho | 1 | 46 | 11.21 |
| Euiyoung Kang | 2 | 31 | 3.85 |
| Hanil Kim | 3 | 96 | 13.34 |
| Hyungchul Kim | 4 | 18 | 5.30 |
| Young-Seok Lee | 5 | 438 | 54.04 |
| Seungdo Jeong | 6 | 25 | 8.82 |