• Asia Marketing Journal
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• v.5 no.4
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• pp.72-90
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• 2003

웅진식품은 우리음료의 자존심을 지키는 세계적인 마실거리 문화기업으로의 기업비젼을 바탕으로 제품개발을 해왔으며, 앞으로 우리의 음료를 가지고 서양음료중심의 세계시장에서 동양음료의 시장을 개척하고자 한다. 기존의 서양음료시장의 시장구조를 깨는 새로운 형태의 음료를 개발하는 제품전략을 가지고 있으며, 자체 유통망이 경쟁사에 비하여 약하기 때문에 대형할인점과 같은 신유통에서의 강점을 살리고자 노력하였고, 가격은 기존경쟁제품보다 약간 비싸게 형성하였다. 단순한 광고도 하지만 우리의 문화를 강조하는 여러가지 커뮤니케이션 전략을 구사하고 있고, 우리음료의 세계화를 위하여 동남아시장을 우선적으로 공략할 예정이다. 지금까지 가을대추, 아침햇살, 초록매실 등 많은 힛트상품을 가지고 300명정도의 적은 인원으로 2500억의 매출을 올리고 있고, 중견기업으로의 성장을 위하여 필요한 시스템을 구축을 위해 ERP둥의 프로세스 정비를 추진하고 있다.

• Proceedings of the Korean Society for Information Management Conference
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• 1996.08a
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• pp.57-60
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• 1996

전문데이터베이스는 원문의 접근가능성과 전문탐색의 장점으로 인해 최근 급속하게 발전하고 있다. 그러나 이제까지 대부분의 전문데이터베이스는 문헌의 구조를 고려하지 않고 본문의 문자열에서 자동추출한 색인어를 대상으로 비통제탐색방법을 사용하여 왔으므로 효율적이고 다양한 검색방법을 적용하기 어려웠다. 본 연구에서는 SGML을 이용하여 문헌을 구조화하고 이를 이용한 색인시스템을 설계함으로써, 문헌구조를 이용한 다양한 검색이 가능하도록 하였다. 이를 위해 논문을 대상으로 하여 문헌의 구조를 분석하고, 주요 문헌요소인 초록, 목차, 본문, 참고문헌의 특성을 색인에 반영하였다. 색인시스템은 문헌요소를 태그와 텍스트데이터로 분석하여 색인하는 일차색인과, 일차색인에 의해 만들어진 문헌요소테이블과 내용데이터파일을 이용하여 주요 문헌요소를 색인한 이차색인으로 구성된다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.191-207
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• 2017

This paper employs entitymetrics analysis on the research works of Dong-ju Yun. He was a Korean poet who was studied by many researchers on his works, religion and life. We collected 1,076 papers about Dong-ju Yun and conducted various approaches including co-author citation analysis, topic modeling analysis to identify the topic trend in the study of Dong-ju Yun. Also we extracted entities like person's name and literature's title from abstract to examine the relationship among them. The result of this paper enables us to objectively identify the topic trend and infer implicit relationships between key concept associated with Dong-ju Yun based on text data. Moreover, we observed sub-research topics such as life, poem, aesthetic existence, comparative literature, literary translation, and religious beliefs. This paper shows how entitymetrics can be utilized to study intellectual structures in the humanities.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.153-176
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• 1993

Structual ambiguity is one of those problem that arise in the analysis of natural language sentences.It has been considered very difficult to solve the problem.Structural ambiguity,however,should be resolved no matter how difficult it may be.Otherwise natural language processing could be virtually impossible.A statistical approach to structural disambiguation is proposed in this dissertation.The information-theoretic concept of mutual information has been empolyed in resolving structural ambiguity Mutual information can be acquired in an automatic way.from text corpora. If a structural disambiguation subsystem had the capability of self-evaluating whether the results of structural disambiguation are correct or not.it would be possible to develop a more intelligent natural language proessing system.In this paper,the concept of confidence measure is also proposed to endow the disambiguation subsystem with such intelligence.Confidence measure is a numeric value calculated after structural disambiguation. Some experiments were performed in order to show the validity of the approach.Mutual information was auto matically acquired from a corpus of 1.6milion words that were collected from scientific abstracts.The accuracy of structural disambiguation was 80%when performed over 1,639 test sentences.Notice that there was no manual tuning in advance for the experiments.The task of detecting and correcting errors in structural disambiguation will be performed very effectively if the concept of confidence measure is employed in the process.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.108-115
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• 2001

In this paper we are attempted to quantitative classification of the three object color regions on a RGB image using of an improved ML(Maximum Likelihood) classification method. A RGB color image consists of three bands i.e., red, green and blue. Therefore it has a 3 dimensional structure in view of the spectral and spatial elements. The 3D structural yokels were projected in RGB cube wherefrom the ML method applied. Between the conventionally and easily usable Box classification and the statistical ML classification based on Bayesian decision theory, we compared and reviewed. Using the ML method we obtained a good segmentation result to classify positive cell nucleus, negative cell Nucleus and background un a immuno-histological breast carcinoma image. Hopefully it is available to diagnosis and prognosis for cancer patients.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.247-267
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• 2011

The purpose of this study is to investigate knowledge structure of knowledge organization research area in Korea. The study employed content analysis and network analysis to analyze degree centrality, betweenness, and eigenvector as well as frequency of words. It also analyzes research articles published during the period of 2000-2001. The study can be summarized that the network of keywords of knowledge organization researches is compact and complicated. Cataloging and classification play important roles in the network, and metadata and ontology becomes focal areas in knowledge organization. On the other hand, networks of authorships and authors are broad and fragmented. Collaboration is not active enough.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.587-598
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• 2003

This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.

• Journal of Information Management
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• v.43 no.2
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• pp.43-66
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• 2012

The purpose of this study is to see the intellectual structure in the field of veterinary sciences in Korea, using author profiling analysis(APA), a bibliometric approach. Three journals are selected on the basis of citation data, exchanging most citations with Korean Journal of Veterinary. And then, 50 authors who published most articles at selected journals during the given period of time were chosen. The analysis of similarity and dissimilarity among authors by comparing co-word appearance patterns from article title, abstracts, and keywords was made. Authors can be grouped 11 minor clusters under 4 major clusters, depending on their interests in the area of veterinary sciences in Korea. The subjects for each cluster at the veterinary sciences are decided by the matching the keyword, representing author's research interest. As a result, it is possible to figure out the current research trends and the researcher network in the field of veterinary sciences.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.154-157
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• 2011

본 연구는 2인의 전문의와 함께 의료 문헌의 초록을 분석하여 의료문서에서의 절차적 지식을 모델링하고 텍스트 마이닝 기법을 적용하여 절차적 지식을 추출하는 방법론에 대해 기술한다. 절차적 지식은 목적과 해법의 묶음으로, 해법은 다시 단위 절차 지식의 네트워크로 정의 하였고, 목적과 해법 정보 추출과 단위 절차 지식의 구성요소인 대상/행위/방법 개체를 인식하기 위해, 품사태깅, 구문분석, 술어-논항구조(Predicate-Argument Structure), 온톨로지 용어 매핑 정보 등에 기반한 기계학습 방법을 사용하였다. 실험을 위해 전문의와 함께 위함과 척추질환에 대한 1309 문서에 절차적 지식 태깅을 수행하였고, 이 문서 집합을 기반으로 목적/해법 추출 작업과 단위 절차 지식(대상질병/행위/적용방법) 추출 실험을 수행하여, 각각 82% 와 63%의 F-measure 값을 얻을 수 있었다.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.816-833
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• 1999

스타일 정보를 중심으로 하는 기존의 워드 프로세서의 출력 문서들을 차세대 인터넷 문서인 XML문서방식에 따라서 표기하고 또한 제목, 초록, 장 및 단락 등과 같은 논리적인 구조를 반영할 수 있도록 구조화함으로써 문서들의 상호교환뿐만 아니라 인터넷에서 유효하게 사용할 수가 있다. 본 논문에서는 스타일 또는 표현 속성 중심으로 하는 다양한 문서의 평면 구조를 XML의 계층적인 논리적인 구조로, 또한 다양한 DTD(Document Type Definition)환경하에서 변경시킬 수가 있는 변환 스크립트 언어를 표현할 수 있도록 하기 위하여 XTML(XML Transformation Markup Language)을 DTD형식으로 정의하고 이를 이용하여 변환 스크립트를 작성하였으며 자동태깅에 적용하여 보았다.XTML은 그 인스턴스에 해당하는 변환 알고리즘의 효과적인 수행을 위하여 즉 기존의 XML문서를 효과적으로 다루기 위하여 문서를 GROVE라는 트리 구조로 만들어 저장하고 또한 이를 조작할 수 있는 기능 및 다양한 명령어 인터페이스를 제공하였다. Abstract Output documents of existing word processors based on style informations or presentation attributes can be structured by converting them into XML(Extensible Markup Language) documents based on hierarchically logical structures such as title, abstract, chapter and so on. If so, it can be very useful to interchange and manipulate documents under Internet environment. The conversion need the complicate process calling auto-tagging by which elements of output documents can be inferred from style informations and sequences of text etc, and which is different from various kinds of simple conversion.In this paper, we defined XTML(XML Transformation Markup Language) of DTD(Document Type Definition) form and also defined the script language as instances of its DTD for the auto-tagging. XTML and its DTD are represented in XML syntax.Especially XTML includes various functions and commands to generate tree structure named as "GROVE" and also to process, store and manipulate the GROVE in order to process efficiently XML documents.documents.