Presentation 2001/7/9
Automatic disabbreviation by usingcontext information
Akira Terada, Takenobu Tokunaga,
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Abstract(in English) Unknown words such as proper nouns, abbreviations, and acronyms are a major obstacle in text processing. In particular, abbreviations are often used in specific domains. In this paper, we propose an automatic disabbreviation method using context information. In past research, a dictionary has conventionally been used to search abbreviation expansion candidates for an abbreviation. We use an abbreviation-poor text of the same domain instead of a dictionary. We calculate the plausibility of expansion candidates based on the similarity between the context of a target abbreviation and that of its expansion candidates. The similarity is calculated using the vector space model, in which each vector element consists of surrounding words. Experiments using about 10,000 documents in the aviation domain showed that the proposed method is superior to past methods by 10% in precision.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) unknown words / abbreviation / context information
Paper # NLC2001-14
Date of Issue

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Committee NLC
Conference Date 2001/7/9(1days)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Automatic disabbreviation by usingcontext information
Sub Title (in English)
Keyword(1) unknown words
Keyword(2) abbreviation
Keyword(3) context information
1st Author's Name Akira Terada
1st Author's Affiliation Department of Computer Science Tokyo Institute of Technology()
2nd Author's Name Takenobu Tokunaga
2nd Author's Affiliation Department of Computer Science Tokyo Institute of Technology
Date 2001/7/9
Paper # NLC2001-14
Volume (vol) vol.101
Number (no) 189
Page pp.pp.-
#Pages 7
Date of Issue