Mining atomic Chinese abbreviations with a probabilistic single character recovery model.
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| Title: | Mining atomic Chinese abbreviations with a probabilistic single character recovery model. |
|---|---|
| Authors: | Jing-Shin Chang1 jshin@csie.ncnu.edu.tw, Wei-Lun Teng1 s3321512@ncnu.edu.tw |
| Source: | Language Resources & Evaluation. Aug2006, Vol. 40 Issue 3/4, p367-374. 8p. |
| Subjects: | Chinese writing, Chinese abbreviations, Chinese characters, Jargon (Terminology), Language dictionaries |
| Geographic Terms: | China |
| Abstract: | An HMM-based single character recovery (SCR) model is proposed in this paper to extract a large set of atomic abbreviations and their full forms from a text corpus. By an “atomic abbreviation,” it refers to an abbreviated word consisting of a single Chinese character. This task is important since Chinese abbreviations cannot be enumerated exhaustively but the abbreviation process for compound words seems to be compositional. One can often decode an abbreviated word character by character to its full form. With a large atomic abbreviation dictionary, one may be able to handle multiple character abbreviation problems more easily based on the compositional property of abbreviations. [ABSTRACT FROM AUTHOR] |
| Copyright of Language Resources & Evaluation is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 27201181 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Mining atomic Chinese abbreviations with a probabilistic single character recovery model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jing-Shin+Chang%22">Jing-Shin Chang</searchLink><relatesTo>1</relatesTo><i> jshin@csie.ncnu.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Wei-Lun+Teng%22">Wei-Lun Teng</searchLink><relatesTo>1</relatesTo><i> s3321512@ncnu.edu.tw</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Language+Resources+%26+Evaluation%22">Language Resources & Evaluation</searchLink>. Aug2006, Vol. 40 Issue 3/4, p367-374. 8p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Chinese+writing%22">Chinese writing</searchLink><br /><searchLink fieldCode="DE" term="%22Chinese+abbreviations%22">Chinese abbreviations</searchLink><br /><searchLink fieldCode="DE" term="%22Chinese+characters%22">Chinese characters</searchLink><br /><searchLink fieldCode="DE" term="%22Jargon+%28Terminology%29%22">Jargon (Terminology)</searchLink><br /><searchLink fieldCode="DE" term="%22Language+dictionaries%22">Language dictionaries</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: An HMM-based single character recovery (SCR) model is proposed in this paper to extract a large set of atomic abbreviations and their full forms from a text corpus. By an “atomic abbreviation,” it refers to an abbreviated word consisting of a single Chinese character. This task is important since Chinese abbreviations cannot be enumerated exhaustively but the abbreviation process for compound words seems to be compositional. One can often decode an abbreviated word character by character to its full form. With a large atomic abbreviation dictionary, one may be able to handle multiple character abbreviation problems more easily based on the compositional property of abbreviations. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Language Resources & Evaluation is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10579-007-9026-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 367 Subjects: – SubjectFull: Chinese writing Type: general – SubjectFull: Chinese abbreviations Type: general – SubjectFull: Chinese characters Type: general – SubjectFull: Jargon (Terminology) Type: general – SubjectFull: Language dictionaries Type: general – SubjectFull: China Type: general Titles: – TitleFull: Mining atomic Chinese abbreviations with a probabilistic single character recovery model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jing-Shin Chang – PersonEntity: Name: NameFull: Wei-Lun Teng IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2006 Type: published Y: 2006 Identifiers: – Type: issn-print Value: 1574020X Numbering: – Type: volume Value: 40 – Type: issue Value: 3/4 Titles: – TitleFull: Language Resources & Evaluation Type: main |
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