• Title/Summary/Keyword: 용어 통합

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Comparative analysis of inter-Korean acoustic terminology and proposal for integration (남북한 음향학 전문용어 비교 분석 및 통합안 제시)

  • Jiwan Kim
    • 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.

Design and Development of a System for Mapping of Medical Standard Terminologies (표준 의학 용어체계의 매핑을 위한 시스템의 설계 및 개발)

  • Lee, In-Keun;Kim, Hwa-Sun;Cho, Hune
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.2
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    • pp.237-243
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    • 2011
  • Various standard terminologies in medical field are composed individually to different structure. Therefore, information on crosswalking between the terminologies is needed to combine and use the terminologies. Lots of mapping tools have been developed and used to create the information. However, since those tools deal with specific terminologies, the information is restrictly created. To overcome this problem, some tools have been developed, which perform mapping tasks by composing various terminologies. However, the tools also have difficulty of composing automatically the terminologies because the terminologies have different structures. Therefore, in this paper, we propose a method for composing and using the terminologies in the developed mapping system with keeping the original structure of the terminologies. In the proposed method, additional terminologies could be added on the mapping system and used by making metadata involving information on location and structure of the terminologies. And the mapping system could cope flexibly with the changes of the structure or context of the terminologies. Moreover, various types of mapping information could be defined and created in the system because mapping data are constructed as triplets in ontology. Therefore, the mapping data can be transformed and distributed in different formats such as OWL, RDF, and Excel. Finally, we confirmed the usefulness of the mapping system based on the proposed method through the experiments about creating mapping data.

A Method for Automatic Extract ion of Term Definition from Text (텍스트로부터 용어 정의문의 자동 추출 방법)

  • Shin, Hyo-Shik;Kim, Jae-Ho;Lee, Hae-Yun;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 2002.10e
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    • pp.292-299
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    • 2002
  • 본 연구는 텍스트 코퍼스로부터 용어의 정의를 자동으로 추출하여 용어의 자동 추출기술과 통합하여 다목적의 용어뱅크를 구축하기 위한 목적으로부터 출발하였다. 지식정보의 확산에 따라 기존 전문분야 용어집에 수록되지 알은 용어의 수는 폭발적으로 증가하고 있다. 기존의 용어집 혹은 용어사전의 디지털화만으로는 새로운 전문용어의 포괄성에서 한계가 있는 것이다. 정보의 획득이라는 면에서 보면 이러한 한계를 극복하고 모든 용어에 대해서 즉시적으로 용어의 정의를 제공받는 것이 바람직하다. 자동으로 구축된 용어집의 응용은 여러 가지로 기대된다. 새로운 용어에 대한 의미 파악을 위해서는 물론, 확장된 전문용어집의 작성이나 전문분야 온톨로지의 구축 등에도 이용될 수 있다.

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Development of an Associative Value Knowledge Base based on UMLS & LOINC Database for Semantic Medical Information Integration. (의미적 의료정보 통합을 위한 UMLS와 LOINC DB 기반의 연관 값 지식베이스 개발)

  • Kim, Tae-Woo;Hong, Dong-Wan;Yoon, Jee-Hee
    • Annual Conference of KIPS
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    • 2003.05c
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    • pp.1551-1554
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    • 2003
  • 최근 다양한 의료정보 시스템이 개발되어, 그 사용이 급증하고 있다. 이 들 각각의 의료정보 시스템에서 발생, 축적된 의료정보는 분산 이질의 형태를 가지며, 또한 같은 의미를 갖는 의료정보가 각기 다른 구조와 용어로 기술되어 축적되는 것이 일반적이다. 이와 같이 개별적으로 개발, 활용되어 온 의료정보를 웹 상에서 통합하여, 단일화 된 의료정보 검색 기능을 제공하기 위해서는 이들 의료정보의 의미적 연관성을 고려한 정보의 통합, 검색 기술의 개발이 필수적이다. 본 논문에서는 의미적 의료정보의 통합을 위한 UMLS와 LOINC 데이터베이스 기반의 연관 값 지식베이스의 설계 및 개발 방식을 제안한다. 웹 상에 존재하는 각종 분산 이질 형태의 의료정보는 XML을 공통 데이터 구조로 하여 통합되며, 정보 통합의 과정에서 연관 값 지식베이스를 참조하여 의미적 관련도가 높은 의료정보(구조 정보와 내용 정보)는 상호 연결되어, 진정한 의미의 정보 통합을 구현하게 된다. 지식베이스는 용어별로 식별자, 요소명, 연관값, 복수형, 동의어, 한글 이름 등의 필드틀 가지며, 현재 상담, 처방, 보험, 의료용어, 증상, 임상결과 등 적용분야 별로 작성된 연관 값 지식베이스가 구현되어 있다.

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Building and Analysis of Semantic Network on S&T Multilingual Terminology (과학기술 전문용어의 다국어 의미망 생성과 분석)

  • Jeong, Do-Heon;Choi, Hee-Yoon
    • Journal of Information Management
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    • v.37 no.4
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    • pp.25-47
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    • 2006
  • A terminology system capable of providing interpretations and classification information on a multilingual science and technology(S&T) terminology is essential to establish an integrated search environment for multilingual S&T information systems. This paper aims to build a base system to manage an integrated information system for multilingual S&T terminology search. It introduces a method to build a search system for S&T terminologies internally linked through the multilingual semantic network and a search technique on the multiple linked nodes. In order to provide a foundation for further analysis researches, it also attempts to suggest a basic approach to interpret terminology clusters generated with those two search methods.

A Study on the Integration of Recognition Technology for Scientific Core Entities (과학기술 핵심개체 인식기술 통합에 관한 연구)

  • Choi, Yun-Soo;Jeong, Chang-Hoo;Cho, Hyun-Yang
    • 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.

Analyzing the Effect of Characteristics of Dictionary on the Accuracy of Document Classifiers (용어 사전의 특성이 문서 분류 정확도에 미치는 영향 연구)

  • Jung, Haegang;Kim, Namgyu
    • Management & Information Systems Review
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    • v.37 no.4
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    • pp.41-62
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    • 2018
  • As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

An Integrated Ontological Approach to Effective Information Management in Science and Technology (과학기술 분야 통합 개념체계의 구축 방안 연구)

  • 정영미;김명옥;이재윤;한승희;유재복
    • Journal of the Korean Society for information Management
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    • v.19 no.1
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    • pp.135-161
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    • 2002
  • This study presents a multilingual integrated ontological approach that enables linking classification systems. thesauri. and terminology databases in science and technology for more effective indexing and information retrieval online. In this integrated system, we designed a thesaurus model with concept as a unit and designated essential data elements for a terminology database on the basis of ISO 12620 standard. The classification system for science and technology adopted in this study provides subject access channels from other existing classification systems through its mapping table. A prototype system was implemented with the field of nuclear energy as an application area.

Recognizing Biomedical Terminologies through Integration of Heterogeneous Information (정보통합을 통한 생물/의학 분야 전문용어의 자동 추출)

  • 오종훈;최기선
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10a
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    • pp.775-777
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    • 2004
  • 전문용어란 전문분야의 개념이 언어적으로 표현된 형태이다. 전문분야마다 분야 특성적인 개념이 사용되므로, 전문용어는 전문분야를 특성화하는 단위로 사용된다. 따라서 전문분야문서에 대한 자연언어처리에서 전문용어를 효과적으로 처리하는 것은 매우 중요하다. 전문용어 추출은 분야 특성적인 전문용어를 해당 분야 문서에서 파악하는 작업을 말한다. 본 논문에서는 기계학습방법을 이용한 전문용어 자동 추출 기법을 제안한다. 본 논문의 기법은 전문분야 사전과 전문분야 문서를 이용하여 문서에서 나타나는 전문용어의 특성을 파악하고 이를 이용하여 전문용어를 추출한다. 본 논문의 기법은 GENIA 2.01 문서에 대하여 86%의 정확률과 90%의 재현율을 나타내었다. 또한 기존연구보다 최고 21%의 성능향상을 나타내었다.

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