Presentation 2004/11/28
Semi-supervised sentence classification for MEDLINE documents(Medical Data Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
TAKAHIKO ITO, MASASHI SHIMBO, TAKAHIRO YAMASAK, YUJI MATSUMOTO,
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Abstract(in English) We address the task of sentence classification in Medline abstracts, in which sentences must be classified into their structural roles such as background, objective, methods, experimental results, and conclusions. With a plenty of labeled data, supervised learning would be able to accurately infer the structural roles of each sentence in the abstracts. However, it is not practical to assume abundant training data as they are expensive to construct. We therefore apply semi-supervised learning to this sentence classification task to remedy the lack of training data. Experimental results show that semi-supervised learning outperform pure supervised learning, when only a small amount of correctly labeled sentences are available.
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Paper # AI2004-43
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Committee AI
Conference Date 2004/11/28(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language ENG
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Title (in English) Semi-supervised sentence classification for MEDLINE documents(Medical Data Mining)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)
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1st Author's Name TAKAHIKO ITO
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name MASASHI SHIMBO
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
3rd Author's Name TAKAHIRO YAMASAK
3rd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology:(Present address)OKI Co.
4th Author's Name YUJI MATSUMOTO
4th Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2004/11/28
Paper # AI2004-43
Volume (vol) vol.104
Number (no) 486
Page pp.pp.-
#Pages 6
Date of Issue