• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.141-160
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• 2004

Recent reseach in the field of medical information systems has paid much attention to an ontology based medical terminology system to support clinical study and effective information search. This study aims to conduct research for further application or construction of ontology systems in Korea. This research reviews the theory of concept modeling and ontology. and analyses 4 cases of conceptual modeling of medical tenrminologies by ontology, The findings ot this study display these specific characteristics in medscal ontologies: (UHe standardization of terrrinology on MeSH. (2) The conceptualization of tenninology on UMLS. (l) ane. (2) are showed as untormal ontologies. (3) The theory of ontology integration in ON9, (4) The reference model of medical knowledge with formalization in GALEN. (3) and (4) are showed as formal ontologies. The application and construction of ontology should be differentiated according to the level of the proposed system, and then this analysis will provide useful information for the researcher and developer of the system.

• 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.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.155-162
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• 2006

The medical thesaurus, MeSH (Medical Subject Heading), has been used as a controlled vocabulary thesaurus for English medical paper indexing for a long time. In this paper, we propose an automatic cross language keyword assignment method, which assigns English MeSH index terms to the abstract of a Korean medical paper. We compare the performance with the indexing performance of human indexers and the authors. The procedure of index term assignment is that first extracting Korean MeSH terms from text, changing these terms into the corresponding English MeSH terms, and calculating the importance of the terms to find the highest rank terms as the keywords. For the process, an effective method to solve spacing variants problem is proposed. Experiment showed that the method solved the spacing variant problem and reduced the thesaurus space by about 42%. And the experiment also showed that the performance of automatic keyword assignment is much less than that of human indexers but is as good as that of authors.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.451-462
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• 2019

Document-term frequency matrix is a type of data used in text mining. This matrix is often based on various documents provided by the objects to be analyzed. When analyzing objects using this matrix, researchers generally select only terms that are common in documents belonging to one object as keywords. Keywords are used to analyze the object. However, this method misses the unique information of the individual document as well as causes a problem of removing potential keywords that occur frequently in a specific document. In this study, we define data that can overcome this problem as proximity data. We introduce twelve methods that generate proximity data and cluster the objects through two clustering methods of multidimensional scaling and k-means cluster analysis. Finally, we choose the best method to be optimized for clustering the object.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.681-693
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• 2022

The purpose of this study is to suggest a plan to utilize atypical data in the health care field by inferring standard medical terms related to the musculoskeletal system through keyword network analysis of medical records of patients hospitalized for musculoskeletal disorders. The analysis target was 145 summaries of discharge with musculoskeletal disorders from 2015 to 2019, and was analyzed using TEXTOM, a big data analysis solution developed by The IMC. The 177 musculoskeletal related terms derived through the primary and secondary refining processes were finally analyzed. As a result of the study, the frequent term was 'Metastasis', the clinical findings were 'Metastasis', the symptoms were 'Weakness', the diagnosis was 'Hepatitis', the treatment was 'Remove', and the body structure was 'Spine' in the analysis results for each medical terminology system. 'Oxycodone' was used the most. Based on these results, we would like to suggest implications for the analysis, utilization, and management of unstructured medical data.

• Proceedings of the Korea Society of Design Studies Conference
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• 2000.11a
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• pp.132-133
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• 2000

오늘날 메타(mee)라는 용어는 '메타언어', '메타과학', '메타비평' 등의 합성어를 통해 자신의 존재를 이 사회에서 확인 받고 있다. 특히 메타언어는 메타라는 용어를 가장 적극적으로 사용하는 경우라고 할 수 있다. 왜냐하면 메타언어는 언어를 연구대상으로 하는 학문영역에서 언어의 한 특성, 흑은 자체의 구조를 설명하는 보다 일반화된 개념으로 소통되고 있기 때문이다. (중략)

• Food Industry
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• s.198
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• pp.59-102
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• 2007

본 자료는 2006년도 식품의약안전청 연구개발사업으로 수해오딘 "제외국의 식품안전정보 수집체계에 관한 비교연구"의 연구결과를 활용하여 제작되었으며, 중국에서 발간된 식품표준 및 법규의 내용을 일부 발췌.번역한 것으로 원문의 용어를 그대로 사용하였기 때문에 우리가 흔히 사용하는 용어와 상이할 수도 있으며 번역상 오류나 부적절한 표현이 있을 수도 있으므로 필요시 원문을 참고하시기 바랍니다.

• Annual Conference on Human and Language Technology
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• 1990.11a
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• pp.49-56
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• 1990

기술개발의 근원인 사고활동을 효과적으로 수행하고, 고도 정보화사회에 대응하는 국가의 지적영역을 확보하기 위해 모든 기술적 개념을 어휘 수준, 구문 수준, 의미수준에서 모국어를 확충 발전시키는 것이 기술 용어의 국어화 과제이다.

• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.5-10
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• 2001

둘 이상의 언어를 포함하고, 그 중 참조하는 언어를 중심으로 용어관계를 표시할 수 있는 다국어 시소러스의 개념구조에 대하여 논하였다. 아울러, 우리말을 기준어로 삼고, 기본요건, 구조화, 용어관계, 동형이의어, 표시방법, 배열 등에 대한 예시와 함께 다국어 시소러스의 설계방안을 제시하였다.

• Proceedings of the Korean Society for Information Management Conference
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• 1995.08a
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• pp.167-170
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• 1995

본고는 ‘정보화 사회’란 용어에 배제된 개념과, 방법론적 오류를 지적하고 우리나라의 경우에 어떻게 정보화사회란 용어가 사용되게 되었으며, 정보와 사회의 관계및 정보화에 대한 사회학적 이해를 바탕으로 정보화 사회의 개념적, 방법론적 문제점 및 부적절성을 분석 제시하고 있다.