Presentation 2006-07-13
Recall Improvement of Technical Term Extraction in the Nursing Domain by Enhancing Permissible Combinations of Word-class
Koji KINAMI, Tetsuo IKEDA, Tsuyoshi TAKAYAMA, Kazuaki TAKEDA,
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Abstract(in English) This paper presents our ongoing research for term extraction from documents in the nursing domain. An exploratory study showed that a well-known term extraction method, which has proven to be effective in extracting term specific to the computing domain, cannot effectively extract words representing symptoms or treatments of diseases. We propose a new term extraction method to improve extraction recall ratio. Its main characteristics are enhancing permissible combinations of word-class; and enhancing morphological analysis logic which is used to analyze the sentences containing sequences of alphabets or katakana.
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Keyword(in English) Term recognition / Domain specific terms / Nursing domain
Paper # DE2006-91
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Committee DE
Conference Date 2006/7/6(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Recall Improvement of Technical Term Extraction in the Nursing Domain by Enhancing Permissible Combinations of Word-class
Sub Title (in English)
Keyword(1) Term recognition
Keyword(2) Domain specific terms
Keyword(3) Nursing domain
1st Author's Name Koji KINAMI
1st Author's Affiliation Graduate School of Software and Information Science, Iwate Prefectural University()
2nd Author's Name Tetsuo IKEDA
2nd Author's Affiliation Department of Software and Information Science, Iwate Prefectural University
3rd Author's Name Tsuyoshi TAKAYAMA
3rd Author's Affiliation Department of Software and Information Science, Iwate Prefectural University
4th Author's Name Kazuaki TAKEDA
4th Author's Affiliation Faculty of Nursing, Iwate Prefectural University
Date 2006-07-13
Paper # DE2006-91
Volume (vol) vol.106
Number (no) 149
Page pp.pp.-
#Pages 6
Date of Issue