Fuzzy ranking model based on user preference
- Authors
- Kang, BY; Kim, Dae-Won; Li, Q
- Issue Date
- Jun-2006
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- fuzzy similarity measure; relevance ranking; information retrieval
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E89D, no.6, pp 1971 - 1974
- Pages
- 4
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E89D
- Number
- 6
- Start Page
- 1971
- End Page
- 1974
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/24338
- DOI
- 10.1093/ietisy/e89-d.6.1971
- ISSN
- 0916-8532
- Abstract
- A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. However, these conventional fuzzy ranking models have a limited ability to incorporate the user preference when calculating the rank of documents. To address this issue, in this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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