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On using category experts for improving the performance and accuracy in recommender systems
- Title
- On using category experts for improving the performance and accuracy in recommender systems
- Authors
- Hwang W.-S.; Lee H.-J.; Kim S.-W.; Lee M.
- Ewha Authors
- 이민수
- SCOPUS Author ID
- 이민수
- Issue Date
- 2012
- Journal Title
- ACM International Conference Proceeding Series
- Citation
- ACM International Conference Proceeding Series, pp. 2355 - 2358
- Indexed
- SCOPUS
- Document Type
- Conference Paper
- Abstract
- A variety of recommendation methods have been proposed to satisfy the performance and accuracy; however, it is fairly difficult to satisfy both of them because there is a trade-off between them. In this paper, we introduce the notion of category experts and propose the recommendation method by exploiting the ratings of category experts instead of those of the users similar to a target user. We also extend the method that uses both the category preference of a target user and his/her similarity to category experts. We show that our method significantly outperforms the existing methods in terms of performance and accuracy through extensive experiments with real-world data. © 2012 ACM.
- DOI
- 10.1145/2396761.2398639
- ISBN
- 9781450311564
- Appears in Collections:
- 인공지능대학 > 컴퓨터공학과 > Journal papers
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