• Journal of the Korean Society for Library and Information Science
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• v.35 no.1
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• pp.143-162
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• 2001

As technical intellectual work now has become prolific and various, rapid evolution of technical terms needs to collect and manage them systematically and efficiently. The purpose of this study is to suggest the microstructure for systematic definitions of definiendum in terminological dictionaries. This study reveals specific properties or differences of terminography on the basis of terminology and lexicography, analyzes problems of microstructure in a current terminological dictionary, and, based upon the theoretical and practical analysis, attempts to derive structural and methodical suggestions for microstructure of terminological dictionaries.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.271-284
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• 2023

This study compared 431 acoustic terminology of South Korean industrial standards and North Korean national standards based on IEC 60050-801:1994 international standards. In addition, this study attempted to integrate acoustic terminology between the two Koreas. There were 139 (32.3 %) AA types with exactly the same form of terminology, 35 (8.1 %) Aa types with different spellings due to differences in linguistic norms, and 257 (59.6 %) AB types with completely different forms. Morphologically, there were more than twice as many different types of terminology as the same type. In the integration of acoustic terminology with different forms, 178 (61 %) North Korean terminology and 76 (26 %) South Korean terminology were adopted. we would like to overcome the limitations of this study through the following suggestions. First, the government should support academic exchanges between the two Koreas and encourage the establishment of common standards for acoustic terminology. Second, efforts should be made to share acoustic terminology data between the two Koreas and publish an integrated acoustic terminology dictionary. Third, South and North Korea should jointly launch a terminology committee to make efforts to revise international standards together.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.158-162
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• 2005

지식의 확산과 대중화로 인하여 동일한 개념에 대한 검증되지 않은 용어들이 난립하고 있다. 종전에는 해당 학 회의용어심의위원회, 혹은 전문가 그룹의 합의를 통해서 출판된 전문용어집이 권위를 가지고 전문용어의 사용을 통제하였었다. 그러나 이제는 기존 전문용어집에 수록되지 않은 새로운 개념을 위한신조어의 생성에 있어서 사용자의 자의적인 해석이 빈번해져서 사회적 합의에 도달하지 못한 새로운 전문용어들이 경쟁적으로 사용되는 추세이다. 이러한 현실에 직면하여 국내외적으로 전문용어의 정비 및 표준화 사업은 언어 및 학문 분야의 경계를 넘어 총체적으로 전략적 접근을 시도하고 있다. 이에 본 연구에서는 7가지의 전문용어 표준화 지침을 수립하고, 그에 따라 ISO 2382의 4030개 정보기술용어를 표준화하고자 한다.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.81-99
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• 2017

Technical documents are important research outputs generated by knowledge and information society. In order to properly use the technical documents properly, it is necessary to utilize advanced information processing techniques, such as summarization and information extraction. In this paper, to extract core information, we automatically extracted the terminologies and their definition based on definitional sentences patterns and the structure of technical documents. Based on this, we proposed the system to build a specialized terminology dictionary. And further we suggested the personalized services so that users can utilize the terminology dictionary in various ways as an knowledge memory. The results of this study will allow users to find up-to-date information faster and easier. In addition, providing a personalized terminology dictionary to users can maximize the value, usability, and retrieval efficiency of the dictionary.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.425-427
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• 2010

Large-scaled information extraction consists of named-entity recognition, terminology extraction and relation extraction. Since all the elementary technologies have been studied independently so far, test collections for related machine learning models also have been constructed independently. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we integrate named-entities and terminologies with PLOT(Person, Location, Organization, Terminology) in a biomedical domain and construct a test collection of PLOT and relations between PLOTs.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.89-104
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• 2011

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In order to extract these entities automatically from scientific documents at once, we developed a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer and terminology extractor.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.329-338
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• 2011

Terminology recognition system which is a preceding research for text mining, information extraction, information retrieval, semantic web, and question-answering has been intensively studied in limited range of domains, especially in bio-medical domain. We propose a domain independent terminology recognition system based on machine learning method using dictionary, syntactic features, and Web search results, since the previous works revealed limitation on applying their approaches to general domain because their resources were domain specific. We achieved F-score 80.8 and 6.5% improvement after comparing the proposed approach with the related approach, C-value, which has been widely used and is based on local domain frequencies. In the second experiment with various combinations of unithood features, the method combined with NGD(Normalized Google Distance) showed the best performance of 81.8 on F-score. We applied three machine learning methods such as Logistic regression, C4.5, and SVMs, and got the best score from the decision tree method, C4.5.

• Journal of Information Management
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• v.40 no.4
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• pp.1-22
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• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.1
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• pp.1-8
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• 2023

The purpose of this study is to find terms that can give identity to the major and occupation of clinical laboratory technologist (also known as medical technologist). The term clinical pathology includes all branches of pathology, namely anatomical pathology, chemical pathology, hematology, microbiology, and all respective subspecialties. Unfortunately, several countries exclude anatomical pathology from the term clinical pathology, a problem that gets compounded when the title is translated into languages other than English. Clinical pathology (US, UK) is a medical specialty. Similar terms are laboratory medicine (Germany, Poland), medical/clinical biology (France, Netherlands) or clinical analysis (Spain). Depending on the person questioned, medical technology is defined slightly differently by individuals, companies, and institutions. The definition also depends on the language in which the question is asked. Medical technology can be translated to define clinical laboratory technology, allied health sciences, medical equipment, biomedical engineering, and health technology. The terms 'clinical pathology technology and pathological technology' are not used in allied health sciences. The names of 'medical technology·medical technologist' can be replaced by 'biomedical laboratory science·biomedical laboratory technologist' or 'clinical laboratory analysis·clinical laboratory analyst'. In this study, it is proposed to change the name of academic and occupation to 'medical biology·medical biology technologist' that combines the term biomedical.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.3 no.2
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• pp.75-97
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• 2000

우리 학회에서는 최근에 폐탄광지 복구에 관한 관심이 고조되고 있으며, 특히 금년내 적당한 시기에, 되도록 빠른 시일 안에 폐탄광지 복구에 관한 국제 심포지엄을 개최할 계획을 가지고 있으나, 아직 학회 설립이후 이 분야에 관한 연구활동이 다소 일천하므로 기초자료준비가 미진한 상태에 있는 현실이다. 이러한 현실적인 상황하에서 필자는 학회의 회장으로서 학회와 회원들의 연구활동지원을 위한 기초적인 자료라도 수집 제공해야 되겠다는 취지를 가지고 이런 저런 일을 진행하고 있다. 이와 같은 학회활동의 하나로 우선 지난 5월 15일부터 20일까지 중국 북경시 신대도(新大都)호텔에서 중국토지학회(中國土地學會) 중국토지부간학회(中國土地復墾學會) 주최로 개최된 "북경 국제토지부간학술연토회(北京 國際土地復墾學術硏討會)" 심포지엄(Beijing International Symposium on Land Reclamation ISLR 2000 - Mine Land Reclamation and Ecological Restoration for 21st Century)에 참석하여 국제적인 상황을 파악할 수 있도록 한 바 있다. 또한 한국의 "폐탄광지역의 산림훼손지 복구 및 폐석유실 방지대책에 관한 고찰" 원고를 우리 학회지에 투고 게재하여 우리 나라의 폐탄광지 복구에 대한 현황을 개략적으로 이해할 수 있도록 하고저 한다. 이와 같은 일을 하다보니, 우리 학회에서도 석탄광산에 관한 전문용어를 파악해야 되겠다는 필요성에 따라서 우선 필자가 가지고 있는 제반 용어자료(참고문헌 제시)를 종합적으로 정리하여 이 용어집을 발표하고자 한다. 이 "소고(小考)" 용어집은 시기적으로 우리 학회 회원들의 필요성에 의해서 편집된 "초고(草稿)" 수준이며, 약 860 용어가 영문 국문(ABC순)/국문 영문(ㄱㄴㄷ순)으로 편집되었다. 이 용어집은 장차 우리 학회에서 용어제정의 기회가 있을 때에는 귀중한 표준 자료로 활용될 수 있을 것이다. 따라서 이 용어집은 우리 학회 제정 표준용어집이 아니라 단순히 필자의 연구자료(안)로 보아야 할 것이다.