• Journal of the Korean earth science society
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• v.31 no.7
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• pp.813-826
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• 2010

The purpose of this study is to investigate discrepant Earth Science terms in high school curriculums and to explore the alternative to those terms. In this study, we defined discrepant terms as different terms which had the same meaning in Earth Science textbooks. Discrepant terms were compared with terms in references and precedent studies, and the preference by 284 of teachers and students was investigated. The results of this study are as follows: A number of discrepant terms were found in references as well as high school textbooks. Participants preferred terms that are more understandable, were learned previously, and were correct to loanword orthography. As for the cases of discrepant terms caused by different notation of proper nouns or different references and background knowledge, the alternative could be explored by the rule of loanword orthography or the journal publications. In conclusion, confusion may be reduced by utilizing common terms that are both based on authorized theory and easy to convey the meaning.

• Annual Conference on Human and Language Technology
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• 1998.10c
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• pp.143-149
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• 1998

한국어 정보검색에서 복합명사와 명사구로 발생하는 색인어와 질의어간의 구문적 용어 불일치는 많은 문제를 일으켜왔다. 본 논문에서는 복합명사 분해와 명사구 정규화를 함께 수행하여 유사도 측정값을 적당히 유지함으로써 재현율을 저하시키지 않고서 정확률을 향상시킬 수 있는 구문적 용어불일치 완화방안을 제시하고자 한다 색인모듈에서는 통계정보를 이용하여 복합명사를 분해하고, 의존관계를 이용하여 명사구를 정규화한다. 분해되고 정규화된 키워드에 경계정보 '/'가 할당되고, 가중치가 계산된다. 검색모듈에서는 경계정보를 이용하여 부분일치를 고려하는 유사도 계산을 수행한다. KTSET 2.0으로 실험한 결과, 제안한 방법은 구문적 용어불일치를 완화할 수 있으며, 재현율을 저하시키지 않고서 정확률을 향상시킬 수 있음을 보인다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3874-3884
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• 2000

An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

• Journal of Korean Ophthalmic Optics Society
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• v.21 no.2
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• pp.83-90
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• 2016

Purpose: The purpose of this study is to compare and analyze keywords of articles in the Korean Ophthalmic Optics Society to MeSH (Medical Subject Headings) terms. The study hopes to enhance the understanding and usage of MeSH and give fundamental information to the Korean Ophthalmic Optics Society in advance. Methods: A total of 1952 keywords from 409 informative articles published from 2004, Vol 9(1) to 2016, Vol 21(1) were compared with MeSH terms according to the criteria of complete coincidence, incomplete coincidence and complete incoincidence. Results: 439 keywords (22.4%) were completely coincident with MeSH terms, 815 keywords (41.8%) were incompletely coincident with MeSH terms and 693 keywords (35.5%) were completely incoincident with MeSH terms. The most used keyword in MeSH terms is in the order of Myopia, Astigmatism and visual acuity. For the incompletely coincident keywords Refractive error, Soft contact lens, and Phoria were used the most. Finally, the most used keywords in the category of completely incoincident were Accommodative lag and Pseudomonas aeruginosa. Conclusions: It is highly recommended that MeSH terms are selected as controlled keywords to increase usage of searced Korean Ophthalmic Optics Society articles in MEDLINE.

• Proceedings of the Korea Database Society Conference
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• 2001.06a
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• pp.311-322
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• 2001

대부분의 일반 정보 검색 시스템은 색인어를 통해 이루어지는데 이런 경우 사용자는 원하는 정보를 얻기 위해 데이터베이스에 저장된 색인어를 정확하게 입력해야 한다. 그러나 일반 사용자가 필요한 색인어를 정확하게 입력하기는 어렵고 특히 원하는 정보가 전문분야의 것일 때는 더욱 그러하다. 따라서 특정 분야의 용어들을 중심으로 전문용어를 관리할 수 있는 시스템의 개발이 요구되고 있다. 정보기술 분야도 빠르게 성장하고 있는 전문분야의 하나로 사용되는 대부분의 단어가 영어이고 한글 표기 또한 다양하여 많은 사용자들이 원하는 정보를 정확하게 찾지 못하고 있다. 이렇듯 단어간의 형태적인 불일치로 인해 생기는 정보 검색의 문제를 해결하고 검색어의 범위를 확장하기 위해 만든 것이 전문용어 검색 시스템이다. 정보 검색시 사용자가 입력한 검색어뿐만 아니라 동의어나 상위어, 하위어까지 검색하여 질의를 확장함으로써 검색 효율을 높일 수 있다. 또한 객체-관계형 데이터베이스로 설계하여 검색이 용이하고, 새로운 단어의 확장이 용이하도록 그 구조를 설계하였다. 제안한 시스템은 메인 메모리 DBMS 를 이용하여 전자상거래와 같이 많은 사용자들이 동시에 접근하는 환경에서도 빠른 검색 성능을 유지할 수 있도록 하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.529-531
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• 2003

전문용어는 전문분야의 개념을 표현하는 언어적 표현이다. 전문용어의 조어단위는 전문용어를 구성하는 최소의 형태적 단위이다. 이러한 조어단위는 전문용어의 의미를 파악하는데 중요할 뿐만 아니라 전문분야 문서에 대한 기계번역과 같은 작업에 중요한 언어자원으로 사용될 수 있다. 하지만‘조어단위와 개념단위의 불일치 문제’, 조어 단위의‘동형이의어’,‘동의이형어’문제 등으로 인하여, 하나의 전문분야 개념을 나타내는 조어단위들의 덩어리를 파악할 필요가 있다. 본 논문에서는 이러한 문제점을 조어분석 된 한영 대역 전문용어사전에 대한 한국어-영어 조어단위 정렬문제로 해결하고자 한다. 본 논문의 기법은 97%의 정확률로 조어단위 간의 정렬을 수행하였다.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.361-378
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• 2011

Since textbooks are developed according to the curriculum, it might be said that the terms registered in curriculum can serve as guidelines for terms used in textbooks. But it really is not. In this study, so that terms registered in curriculum can serve as guidelines for terms used in textbooks, inconsistencies between them would be found out and improved. To this end, suitability of selecting and using terms are discussed, focusing on terms registered in curriculum and terms used in textbooks. In fact, there are significant differences between the terms registered in curriculum and the terms in textbooks, because there is not any criteria in selecting and using terms. In this study the five criteria with respect to registering terms in curriculum are proposed. Everyday language should not be registered. Naturalized terms should not be registered. Terms used in only elementary mathematics, but are already well-established should be registered. Same term used in diverse context should be registered only once. Terms which can be used without definition should be designated. Three criteria in regard to using terms in textbooks are proposed. Terms registered in curriculum must be used. Same term used in diverse context should be redefined in every context. Terms that are not certified and are not absolutely necessary must not be used.

• Journal of The Korean Association For Science Education
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• v.31 no.8
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• pp.1175-1185
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• 2011

Language skills in science education seem to have a great impact on student achievement. Most of the language skills affecting students' science learning can be accounted for an understanding of scientific terms. The ultimate goal of this study is selecting and grading the scientific terms for science education. As a basic research, we investigated scientific terms contained in science textbooks, because they are the most basic and selected terminologies. As a result of investigation of scientific terms in physics units of middle school science textbooks, we made a list of 556 scientific terms by grade level. This includes 249 words for grade 7, 170 words for grade 8, and 137 words for grade 9.

• Education of Primary School Mathematics
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• v.26 no.1
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• pp.15-28
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• 2023

Since mathematical concepts are learned through the meaning of mathematical terms in school mathematics, learners must understand and use mathematical terms appropriately. However, the meaning of mathematical terms used in real life may be perceived differently from elementary mathematics textbooks, and this difference may cause confusion in learners' understanding of mathematical terms. Therefore, this study was intended to compare and analyze the mathematical terms in elementary mathematics textbooks used in Korea and a Korean dictionary. The findings revealed that the meaning of the textbooks was similar or different, and the subject indicated by each meaning was different. In this case, in order to prevent confusion among learners, it is necessary to supplement and guide each meaning by recognizing the difference between the mathematical terms in elementary mathematics textbooks used in Korea and a Korean dictionary.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.300-311
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• 2005

Terms are linguistic realization of technical concepts. Term constituents are important elements used for representing the concept. Since many new terms are created from the modification or combination of existing constituents, it is important to analyze term constituents for understanding the concept of the term. It means that term constituents offer clues for understanding the concept of terms. However, there are a couple of difficulties in matching concept unit and term constituents such as mismatching between a term constituent and a concept unit, homonym of term constituents and synonym of term constituents. To solve them, it is necessary to recognize concept units of term constituents. In this paper, we define an English term constituent as the concept unit and use an alignment algorithm between English-Korean term constituents in order to recognize concept units of term constituents. By our alignment algorithm we recognize Korean term constituents corresponding to an English term constituent with about $93\%$ precision.