Opinion leader based filtering
- Authors
- Cheon, H; Lee, H
- Issue Date
- 2005
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- DIGITAL LIBRARIES: IMPLEMENTING STRATEGIES AND SHARING EXPERIENCES, PROCEEDINGS, v.3815, pp.352 - 359
- Indexed
- SCIE
SCOPUS
- Journal Title
- DIGITAL LIBRARIES: IMPLEMENTING STRATEGIES AND SHARING EXPERIENCES, PROCEEDINGS
- Volume
- 3815
- Start Page
- 352
- End Page
- 359
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/123273
- ISSN
- 0302-9743
- Abstract
- Recommendation systems are helping users find the information, products, and other people they most want to find, therefore many on-line stores provide recommending services e.g. Amazon, CDNOW, etc. Most recommendation systems use collaborative filtering, content-based filtering, and hybrid techniques to predict user preferences. We discuss the strengths and weaknesses of the techniques and present a unique recommendation system that automatically selects opinion leaders by category or genre to improve the performance of recommendation. Finally, our approach will help to solve the cold-start problem in collaborative filtering.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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