• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.457-488
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• 2003

Public records, produced during the period of Government-General of Chosun. are essential sources for Korean modern history research. The purpose of this study is to provide a guideline for developing function-based classification scheme for the records. This present paper begins with analyzing archival principles regarding the function-based classification. and examines the problems of current arrangement practices. Based on these analyses, it suggests a guideline for constructing a classification system and a functional thesaurus for the public records of Government-General of Chosun. This guideline also covers functional analysis process and some considerations of different classification aspects which are conceptual, verbal and notational.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.3
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• pp.57-78
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• 2012

Of the collection of public libraries in Korea, the literature collection is the largest, and Korean fictions, about 14% of the entire collection constitute the largest single subject. However, in the Korean Decimal Classification(KDC) Korean fiction is represented in one section, that is, 813 which corresponds to the only one of thousand divisions. More specifically, only two sub-sections, 813.6 and 813.7 are supposed to be assigned to the huge collection of modern Korean fiction, and, in reality, only 813.6 is being used in most libraries. Even with the use of book numbers, such disproportionate allocation of classification numbers would definitely lower the discriminative capacity of call numbers given to each item. It would also bring about difficulties in both shelving, on the libraries' side, and finding items from shelf, on the users' side. This study aims to examine the issues related to classifying Korean fictions in public libraries, including the composition of KDC schedules and the actual practice of classification, and then proposes the measures for improving the classification of Korean fictions.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.446-453
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• 2013

In this paper, we propose an efficient method to describe and save Jeongganbo score which has various structures and symbols by using XML (Extensible Markup Language). To do this, analysis of Jeongganbo's structures, and classification of symbols for jeongganbo were preformed. Then, Jeongganbo DTD (Document Type Definition) was defined to describe Jeongganbo score in XML document. To verify the proposed method, we produced a Jeongganbo score XML file for real Jeongganbo score according to the proposed Jeongganbo DTD, and then evaluated the produced XML file by using Jeongganbo XML interpreter software which can interpret the Jeongganbo XML file and represent the Jeongganbo score.

• Journal of Korean Library and Information Science Society
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• v.32 no.1
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• pp.223-248
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• 2001

The purpose of this study is to analyze the problems of classified items by directly applying the domestic literary publications of agriculture field one by one and to present revision scheme having KDC as the subject of the study. In order to do this, I directly applied and analyzed KDC's 4th edition to the 5,400 literatures of agricultural field from the collection list database at the National Library of Korea. Revision scheme of KDC's agricultural field that's been made based on the above revision scheme tried to follow the basic classified systems and items of KDC's 4th edition, if possible, and in terns of necessary items, it includes only addition of cycles and the minimum subdivided extension.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.82-85
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• 2008

고객의 기호와 요구에 부응하는 서비스의 제공을 위해 영화 요소 중 정확한 장르의 분류는 고객의 선택에 있어 중요한 문제이다. 기존의 수작업에 의한 장르 분류는 시간과 비용, 신뢰성 등에서 비효율적이다. 이러한 문제의 해결을 위해 영화 시놉시스(Synopsis) 기반의 기계학습 방법은 효율적인 대안이 될 수 있다. 본 논문에서는 대다수 영화서비스 주체가 보유하고 있는 시놉시스 정보를 기반으로 하여 기계학습을 이용한 영화장르 분류에 관한 하나의 정형화된 방법을 제시한다. 기계학습 Algorithm 중 LibSVM, RandomComittee, LMT, NaiveBayes, PART Algorithm 을 이용하여 Algorithm 별, 장르별 분류 정확도를 측정하여 비교한다.

• 기호학연구
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• no.56
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• pp.7-44
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• 2018

The objective of this paper is to propose a classification of Korean taste terms, especially Korean taste adjectives, from the perspective of cognitive science. The classification of Korean taste terms is here grounded in the definition of 'taste sense', 'flavor' and 'taste' which is usually employed in disciplines of cognitive science. There have been a large number of domestic researches in field of taste terms. Accordingly, a lot of research findings on the classification of taste terms have steadily been released showing the differences among researchers. These different classifications are largely based on the fact that researchers have applied their subjective criteria rather than their objective in order to categorize taste terms. According to previous studies, it is well-known that, in everyday usage, the term 'taste' covers a much wider range of qualities than those perceived through the taste receptor cells alone. In addition, we take it for granted that as much as 80~90% of taste comes from olfactory modality. It is also important to note that the texture and temperature of food, the color of food, the sounds of food, and atmospheric cues have an essential effect on taste perception. Many scientists have already pointed out that taste evaluations are influenced by a number of individual and sociocultural factors. Eating and tasting are important parts of our everyday life, so that linguistic approaches to taste perception seem to be of great significance. We can assume that a classification of taste terms from the perspective of cognitive sciences may shed light on the perceptive mechanism through which we perceive taste. It should be noted that this paper is an advanced work prepared for the follow-up study which will try to make a geometric model of word field 'taste terms' existing or probably existing in the mental lexicon of human beings.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.494-496
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• 2010

영화의 리듬은 최종적으로 편집 테이블 위에서 이루어지며 편집 시에는 주요하게 형식상으로 리듬을 처리한다. 형식상 영화 리듬은 내적 리듬과 외적 리듬으로 분류하며 따라서 이 글에서는 주로 영화 내적 리듬과 외적 리듬을 분석하는 각도에서 영화 리듬을 연구하고자 한다.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.334-335
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• 2018

최근 수 년간 비디오 콘텐츠 소비 공간이 인터넷으로 확장되며 지능적 비디오 콘텐츠 추천 기술 개발이 진행되어 왔다. 하지만 지능적 비디오 콘텐츠 추천 기술은 사용자의 기호나 업로드된 비디오 콘텐츠의 제목 등을 기반으로 하여 비디오 콘텐츠 클래스에 대한 분석 없이 유사한 비디오 콘텐츠를 탐색하고 추천해주는 기술이 대부분이다. 본 논문에서는 지능적 콘텐츠 추천을 위한 딥러닝 기반 방송 콘텐츠 클래스 분류 시스템을 제안한다. 방송 콘텐츠 내 영상 정보를 이용하여 방송 콘텐츠 클래스를 분류하며 높은 분류 정확도를 보여주는 것을 확인할 수 있다.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.144-151
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• 2021

딥러닝의 등장으로 자동 음성 인식 (Automatic Speech Recognition) 기술은 인간과 컴퓨터의 상호작용을 위한 가장 중요한 요소로 자리 잡았다. 그러나 아직까지 유사 발음 오류, 띄어쓰기 오류, 기호부착 오류 등과 같이 해결해야할 난제들이 많이 존재하며 오류 유형에 대한 명확한 기준 정립이 되고 있지 않은 실정이다. 이에 본 논문은 음성 인식 시스템의 오류 유형 분류 기준을 한국어에 특화되게 설계하였으며 이를 다양한 상용화 음성 인식 시스템을 바탕으로 질적 분석 및 오류 분류를 진행하였다. 실험의 경우 도메인과 어투에 따른 분석을 각각 진행하였으며 이를 통해 각 상용화 시스템별 강건한 부분과 약점인 부분을 파악할 수 있었다.