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Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication

image of Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication
ISSN 0929-9971
E-ISSN 1569-9994


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  • Methods of automatic term recognition: A review
    • Authors: Kyo Kageura, and Bin Umino
    • Source: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, Volume 3, Issue 2, 1996, pages: 259 –289
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    • Following the growing interest in "corpus-based" approaches to computational linguistics, a number of studies have recently appeared on the topic of automatic term recognition or extraction. Because a successful term-recognition method has to be based on proper insights into the nature of terms, studies of automatic term recognition not only contribute to the applications of computational linguistics but also to the theoretical foundation of terminology. Many studies on automatic term recognition treat interesting aspects of terms, but most of them are not well founded and described.This paper tries to give an overview of the principles and methods of automatic term recognition. For that purpose, two major trends are examined, i.e., studies in automatic recognition of significant elements for indexing mainly carried out in information-retrieval circles and current research in automatic term recognition in the field of computational linguistics.
  • Term extraction using non-technical corpora as a point of leverage
  • A corpus comparison approach for terminology extraction
    • Author: Teresa Mihwa Chung
    • Source: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, Volume 9, Issue 2, 2003, pages: 221 –246
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    • This article examines one of the possible approaches to identifying technical terms: a corpus comparison approach using the range and frequency of word forms. In order to identify terms using the corpus comparison approach, a ratio is used as a tool based on the comparative range and frequency of word forms between a technical corpus and a comparison corpus. A rating scale approach is used as the basis for evaluating the corpus comparison approach.The analysis shows that the corpus comparison approach works reasonably well with around 86% overlap with the results from the rating scale approach. It also shows that the corpus comparison approach using word types is a reasonably simple and practical way of identifying terms.
  • Theories of terminology: Their description, prescription and explanation
    • Author: M. Teresa Cabré Castellví
    • Source: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, Volume 9, Issue 2, 2003, pages: 163 –199
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    • During the past decade, the theory of terminology has been a subject of debate in various circles. This article examines some of the reasons why this topic has been receiving so much interest lately. I will first discuss the theory developed by Wüster and analyse the motivations behind his model. Then, I will explain why the Wüsterian theory was not questioned or challenged for a long time. This will lead us to the reasons why so many critical voices have been raised recently, both from inside traditional viewpoints and outside. I will also look at the reception these new ideas have had in terminology circles. Finally, I will present my own definition of a theory of terminology, by examining important issues such a theory should take into account and see what I can offer to this debate.
  • Automatic term recognition based on statistics of compound nouns
    • Author: Hirosi Nakagawa
    • Source: Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, Volume 6, Issue 2, 2000, pages: 195 –210
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    • The NTCIR1 TMREC group called for participation of the term recognition task which is a part of NTCIR1 held in 1999. As an activity of TMREC, they have provided us with the test collection of the term recognition task. The goal of this task is to automatically recognize and extract terms from the text corpus which consists of 1,870 abstracts gathered from the NACSIS Academic Conference Database. This article describes the term extraction method we have proposed to extract terms consisting of simple and compound nouns and the experimental evaluation of the proposed method with this NTCIR TMREC test collection. The basic idea of scoring a simple noun N of our term extraction method is to count how many nouns are conjoined with N to make compound nouns. Then we extend this score to measure the score of compound nouns because most of technical terms are compound nouns. Our method has a parameter to tune the degree of preference either for longer compound nouns or for shorter compound nouns. As for term candidates, in addition to noun sequences, we may add variations such as patterns of "A no B" that roughly means "B of A" or "A’ś B" and/or "A na B" where "A na" is an adjective. Experimental results of our method are promising, namely recall of 0.83, precision of 0.46 and F-value of 0.59 for exactly matched extracted terms when we take into account top scoring 16,000 extracted terms.
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