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Computer aided term bank creation and standardization: Building standardized term banks through automated term extraction and advanced editing tools
Linköping University, Department of Computer and Information Science, NLPLAB - Natural Language Processing Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, NLPLAB - Natural Language Processing Laboratory. Linköping University, The Institute of Technology.
2010 (English)In: Terminology in Everyday Life / [ed] Marcel Thelen and Frieda Steurs, John Benjamins Publishing Company , 2010, 163-180 p.Chapter in book (Other academic)
Abstract [en]

Using a standardized term bank in both authoring and translation processes can facilitate the use of consistent terminology, which in turn minimizes confusion and frustration from the readers. One of the problems of creating a standardized term bank, is the time and effort required. Recent developments in term extraction techniques based on word alignment can improve extraction of term candidates when parallel texts are available. The aligned units are processed automatically, but a large quantity of term candidates will still have to be processed by a terminologist to select which candidates should be promoted to standardized terms. To minimize the work needed to process the extracted term candidates, we propose a method based on using efficient editing tools, as well as ranking the extracted set of term candidates by quality. This sorted set of term candidates can then be edited, categorized and filtered in a more effective way. In this paper, the process and methods used to arrive at a standardized term bank are presented and discussed.


Place, publisher, year, edition, pages
John Benjamins Publishing Company , 2010. 163-180 p.
, Terminology and Lexicography Research and Practice, ISSN 1388-8455 ; 13
Keyword [en]
terminology, extraction, term bank, automation
National Category
Language Technology (Computational Linguistics) Computer Science
URN: urn:nbn:se:liu:diva-59842ISBN: 978 90 272 2337 1OAI: diva2:353517
Available from: 2010-09-27 Created: 2010-09-27 Last updated: 2013-04-12Bibliographically 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.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1523
terminology, automatic term extraction, automatic term recognition, computational terminology, terminology management
National Category
Language Technology (Computational Linguistics)
urn:nbn:se:liu:diva-75243 (URN)978-91-7519-944-3 (ISBN)
2012-04-04, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Available from: 2012-03-07 Created: 2012-02-23 Last updated: 2012-03-07Bibliographically approved

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