liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Exploring termhood using language models
Linköping University, Department of Computer and Information Science, NLPLAB - Natural Language Processing Laboratory. Linköping University, The Institute of Technology.
2011 (English)In: Proceedings of the Workshop CHAT 2011: Creation, Harmonization and Application of Terminology Resources / [ed] Tatiana Gornostay, Andrejs Vasiljevs, Tartu University Library (Estonia): Northern European Association for Language Technology (NEALT) , 2011, 32-35 p.Conference paper, Published paper (Refereed)
Abstract [en]

Term extraction metrics are mostly based on frequency counts. This can be a problem when trying to extract previously unseen multi-word terms. This paper explores whether smoothed language models can be used instead. Although a simplistic use of language models is examined in this paper, the results indicate that with more refinement, smoothed language models may be used instead of unsmoothed frequency-count based termhood metrics.

Place, publisher, year, edition, pages
Tartu University Library (Estonia): Northern European Association for Language Technology (NEALT) , 2011. 32-35 p.
Series
NEALT Proceedings Series, ISSN 1736-8197, E-ISSN 1736-6305 ; Vol. 12
Keyword [en]
automatic term extraction, computational terminology, machine learning
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:liu:diva-75238OAI: oai:DiVA.org:liu-75238DiVA: diva2:505124
Conference
NODALIDA 2011 Workshop Creation, Harmonization and Application of Terminology Resources, May 11, 2011, Riga, Latvia
Available from: 2012-02-23 Created: 2012-02-22 Last updated: 2017-02-21Bibliographically approved
In thesis
1. Computational Terminology: Exploring Bilingual and Monolingual Term Extraction
Open this publication in new window or tab >>Computational Terminology: Exploring Bilingual and Monolingual Term Extraction
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Terminologies are becoming more important to modern day society as technology and science continue to grow at an accelerating rate in a globalized environment. Agreeing upon which terms should be used to represent which concepts and how those terms should be translated into different languages is important if we wish to be able to communicate with as little confusion and misunderstandings as possible.

Since the 1990s, an increasing amount of terminology research has been devoted to facilitating and augmenting terminology-related tasks by using computers and computational methods. One focus for this research is Automatic Term Extraction (ATE).

In this compilation thesis, studies on both bilingual and monolingual ATE are presented. First, two publications reporting on how bilingual ATE using the align-extract approach can be used to extract patent terms. The result in this case was 181,000 manually validated English-Swedish patent terms which were to be used in a machine translation system for patent documents. A critical component of the method used is the Q-value metric, presented in the third paper, which can be used to rank extracted term candidates (TC) in an order that correlates with TC precision. The use of Machine Learning (ML) in monolingual ATE is the topic of the two final contributions. The first ML-related publication shows that rule induction based ML can be used to generate linguistic term selection patterns, and in the second ML-related publication, contrastive n-gram language models are used in conjunction with SVM ML to improve the precision of term candidates selected using linguistic patterns.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 68 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1523
Keyword
terminology, automatic term extraction, automatic term recognition, computational terminology, terminology management
National Category
Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:liu:diva-75243 (URN)978-91-7519-944-3 (ISBN)
Presentation
2012-04-04, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2012-03-07 Created: 2012-02-23 Last updated: 2012-03-07Bibliographically approved

Open Access in DiVA

No full text

Other links

Fulltext

Authority records BETA

Foo, Jody

Search in DiVA

By author/editor
Foo, Jody
By organisation
NLPLAB - Natural Language Processing LaboratoryThe Institute of Technology
Language Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 124 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf