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Fuzzy ranking model based on user preference

Authors
Kang, BYKim, Dae-WonLi, 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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Kim, Dae-Won
소프트웨어대학 (소프트웨어학부)
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