• Journal of Information Management
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• v.27 no.4
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• pp.35-56
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• 1996

SGML(Standard Generalized Markup Language) and its application to full-text database including a table, a figure and a picture are explained. A structure of SGML based full-text database Is defined by DTD(document type definition) written in SGML, and full-text itself is described with generalized markup depending on DTD. This article explains how to represent a document structure : a hierarchical structure like a chapter, a section, or a paragraph, or non-hierarchical(referencial) structure like a note, a table, a figure or a picture. Merits of SGML, electronic publishing, a retrieval system or hypertext and SGML tools are also described.

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.5
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• pp.62-66
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• 2001

대중을 대상으로 한 과학정보의 연계체계를 구축하면서 과학분야별, 기관단체별 보유 과학대중화 자료(문헌, 영상, 음성자료)를 조사 및 목록화하고 한국과학문화재단 보유 자료를 포함한 각 기관-단체 발간 문헌자료를 디지털화 시키면서, 기존의 TEXT 위주의 DB에서 사용자가 보다 쉽고 친숙하게 정보를 이용할 수 있도록 DB를 멀티미디어화하여 구축 하므로써 기존의 TEXT 위주의RDB를 택하지 않고, ORDB를 지원하는DBMS중 개발과 운영 및 타DB와 호환이 용이한 DBMS를 도입함으로써 과학분야별로 일반인이 이해하기 쉬운 형태의 자료(텍스트 및 디지털 영상, 음성, 애니메이션, 가상실험등)를 활용한 분야 소개 정보를 구축했다.

• Journal of the military operations research society of Korea
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• v.36 no.1
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• pp.39-49
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• 2010

This paper tries to identify emerging defense technology using S&T Text Mining. As a national agenda, there has been much effort to build S&T information systems including NTIS and DTiMS that enable researchers, policy makers, or field users to analyze technological changes and promote the best policy practices for efficient workflow, knowledge sharing, strategy development, or institutional competitiveness. In this paper, the S&T Text Mining application to unmanned combat technology using INSPEC DB is empirically illustrated and shows that it is a feasible approach to identify emerging defense technology as well as the structure of knowledge network of the future technology candidates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.81-83
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• 2022

Understanding research trends is necessary to select research topics and explore related works. Most researchers search representative keywords of interesting domains or technologies to understand research trends. However some conferences in artificial intelligence or data mining fields recently publish hundreds to thousands of papers for each year. It makes difficult for researchers to understand research trend of interesting domains. In our paper, we propose an automatic technology keyphrase extraction method to support researcher to understand research trend for each conference or journal. Keyphrase extraction that extracts important terms or phrases from a text, is a fundamental technology for a natural language processing such as summarization or searching, etc. Previous keyphrase extraction technologies based on pretrained language model extract keyphrases from long texts so performances are degraded in short texts like titles of papers. In this paper, we propose a techonolgy keyphrase extraction model that is robust in short text and considers the importance of the word.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.742-751
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• 2005

This paper proposes a novel text image watermarking algorithm based on word classification. The words are classified into K classes using simple features. Several adjacent words are grouped into a segment. and the segments are also classified using the word class information. The same amount of information is inserted into each of the segment classes. The signal is encoded by modifying some inter-word spaces statistics of segment classes. Subjective comparisons with conventional word-shift algorithms are presented under several criteria.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.347-350
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• 2012

컴퓨터 프로그래밍 교육은 컴퓨터과학 분야의 관련 전공과목을 공부하기 위하여 매우 중요할 뿐만 아니라, 학생들의 취업을 위한 기술 교육에서도 매우 중요하다. 이 논문에서는 학생들의 교육 및 취업에 적합한 교육용 및 상용 프로그래밍 언어, 도구에 대한 타당성을 분석하여 프로그래밍 교육에 적합한 프로그래밍 언어/도구를 선택하고, 이에 대한 교육 과정을 개발하여 프로그래밍 현장 교육에 적용하고 분석한다. 특히, 최근의 기술 추세와 산업계에 필요한 임베디드/모바일/웹/3D 프로그래밍 분야에 널리 사용되고 있는 프로그래밍 분야에서 텍스트 기반 언어(예: JAVA)와 시각 프로그래밍 언어/환경(예: LabVIEW)에 대한 유용성을 비교하여 분석한다.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.502-511
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• 2005

In this paper, we propose a hybrid analysis method(HAM) based on gray-intensity information from natural scene images. The HAM is composed of GIA(Gray-intensity Information Analysis) and SMA(Split/Merge Analysis). Our experimental results show that the proposed approach is superior to conventional methods both in simple and complex images.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.916-917
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• 2023

본 연구는 사용자의 음성 패턴 분석과 텍스트 분류를 중심으로 이루어지는 한국어 감정 인식 작업을 개선하기 위해 Macaron Net 텍스트 모델의 결과와 MFCC 음성 모델의 결과 가중치 합을 분류하여 최종 감정을 판단하는 기존 82.9%였던 정확도를 텍스트 모델 기준 87.0%, Multi-Modal 모델 기준 88.0%로 개선한 모델을 제안한다. 해당 모델을 우울증 예방 플랫폼의 핵심 모델에 탑재하여 covid-19 팬데믹 이후 사회의 문제점으로 부상한 우울증 문제 해소에 기여 하고자 한다.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.698-702
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• 2017

Since the introduction of Deep Neural Networks to the Natural Language Processing field, two major approaches have been considered for modeling text. One method involved learning embeddings, i.e. the distributed representations containing abstract semantics of words or sentences, with the textual context. The other strategy consisted of composing the embeddings trained by the above to get embeddings of longer texts. However, most studies of the composition methods just adopt word embeddings without consideration of the optimal embedding unit and the optimal method of composition. In this paper, we conducted experiments to analyze the optimal embedding unit and the optimal composition method for modeling longer texts, such as documents. In addition, we suggest a new discourse-based composition to overcome the limitation of the sequential composition method on composing sentence embeddings.

• Journal of KIISE
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• v.42 no.4
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• pp.468-474
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• 2015

Corporations should make efforts to recognize the importance of projects, identify their failure factors, prevent risks in advance, and raise the success rates, because the corporations need to make quick responses to rapid external changes. There are some previous studies on success and failure factors of projects, however, most of them have limitations in terms of objectivity and quantitative analysis based on data gathering through surveys, statistical sampling and analysis. This study analyzes the failure factors of projects based on data mining to find problems with projects in an audit report, which is an objective project evaluation report. To do this, we identified the texts in the paragraph of suggestions about improvement. We made use of the superior classification algorithms in this study, which were NaiveBayes, SMO and J48. They were evaluated in terms of data of Recall and Precision after performing 10-fold-cross validation. In the identified texts, the failure factors of projects were analyzed so that they could be utilized in project implementation.