Fuzzy Ranking Model Based on User Preference(Natural Language Processing)
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概要
- 論文の詳細を見る
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.
- 社団法人電子情報通信学会の論文
- 2006-06-01
著者
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LI Qing
School of Pharmacy, Shenyang Pharmaceutical University
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Kim Dae‐won
Chung‐ang Univ. Seoul Kor
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Kim Dae-won
School Of Computer Science And Engineering Chung-ang University
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KANG Bo-Yeong
Digital Enterprise Research Institute Korea, Seoul National University
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Kang Bo-yeong
Digital Enterprise Research Institute Korea Seoul National University
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Li Qing
School Of Chemistry Dalian University Of Technology
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Li Qing
School Of Engineering Information And Communications University
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