• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.123-142
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• 2022

In 2000, North Korea developed and published a two-volume, <Classification-Search Term Dictionary> and is currently used throughout North Korea. The purpose of this study is to examine the development process of the classification schemes of the North Korea after liberation and to understand the contents, composition, and principles of the <Classification-Search Term Dictionary> published in 2000 and revised in 2014. Until now, all the studies of the North Korean classification schemes were studies on the <Book Classification Scheme> published in North Korea in 1964, and there has been no discussion on North Korea's classification schemes since then. The first volume of the <Classification-Search Term Dictionary> consists of 'classification symbols - search terms', and the second volume consists of 'search terms - classification symbols'. Volume 1 is based on the <Books and Bibliography Classification Scheme (1996)>, and there are a total of 41 main classes in five categories. Volume 1 allocates 1 main class (11/19) to 'revolutionary ideas and theories', 8 main classes (20~27) to 'natural sciences', 19 main classes (30~69) to 'engineering technology and applied sciences', 12 main classes (70~85) to 'social sciences', and 1 main class (90) to 'total sciences'. Volume 2 is similar to subject-headings. North Korea's <Classification-Search Term Dictionary> is the first classification scheme introduced in South Korea and is expected to be the starting point for future studies on the establishment of the standard unification classification schemes.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.1
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• pp.71-92
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• 2000

This study aims to content analysis of Library Classification System in the North Korean. Also This paper is analyze and overview to conceptual framework. Notational system. Principle of hierarchy in the North Korean's Library Classification System. Libraries usually arrange their collections according to the systematic structure of the library classification. A decimal point follows the third digit. After which division by ten continues to the specific degree of classification needed. This system is based on the social and communism thought. The libraries in the South and the North has different concepts, goals, information resources, classification system and the different ways of using them. Considering the practical aspects of the libraries and the reasons for their existence, they must structure the mutual cooperative system so as to minimize the shock when confronting the social changes, so-cold the national unification.

• Proceedings of the Korean Society for Information Management Conference
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• 2003.08a
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• pp.55-64
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• 2003

인터넷 학술정보자원이 급증하고 있는 가운데 자동문헌분류에 대한 관심과 필요성도 늘어가고 있다. 자동문헌분류에 관한 실험은 전처리 단계인 대표색인어 추출과 추출된 대표색인어의 분류성능 평가 실험으로 구분 할 수 있는데, 본 연구에서는 우선 대표색인어 추출을 위해 다양한 대표색인어(자질) 추출 방법에 따른 색인어 성능평가 실험 및 최적의 대표색인어 개수 선정 실험을 수행하였다.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.99-118
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• 2023

The objective of this study is to identify performance factors in the automatic classification of records by utilizing metadata that contains the contextual information of records. For this study, we collected 97,064 records of original textual information from Korean central administrative agencies in 2022. Various classification algorithms, data selection methods, and feature extraction techniques are applied and compared with the intent to discern the optimal performance-inducing technique. The study results demonstrated that among classification algorithms, Random Forest displayed higher performance, and among feature extraction techniques, the TF method proved to be the most effective. The minimum data quantity of unit tasks had a minimal influence on performance, and the addition of features positively affected performance, while their removal had a discernible negative impact.

• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.155-171
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• 2012

In text categorization, core terms of an input document are hardly selected as classification features if they do not occur in a training document set. Besides, synonymous terms with the same concept are usually treated as different features. This study aims to improve text categorization performance by integrating synonyms into a single feature and by replacing input terms not in the training document set with the most similar term occurring in training documents using Wikipedia. For the selection of classification features, experiments were performed in various settings composed of three different conditions: the use of category information of non-training terms, the part of Wikipedia used for measuring term-term similarity, and the type of similarity measures. The categorization performance of a kNN classifier was improved by 0.35~1.85% in $F_1$ value in all the experimental settings when non-learning terms were replaced by the learning term with the highest similarity above the threshold value. Although the improvement ratio is not as high as expected, several semantic as well as structural devices of Wikipedia could be used for selecting more effective classification features.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.3
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• pp.247-264
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• 2021

This study aims to create a deep learning-based classification model to classify suicide tendency by suicide corpus constructed for the present study. Also, to analyze suicide factors, the study classified suicide tendency corpus into detailed topics by using topic modeling, an analysis technique that automatically extracts topics. For this purpose, 2,011 documents of the suicide-related corpus collected from social media naver knowledge iN were directly annotated into suicide-tendency documents or non-suicide-tendency documents based on suicide prevention education manual issued by the Central Suicide Prevention Center, and we also conducted the deep learning model(LSTM, BERT, ELECTRA) performance evaluation based on the classification model, using annotated corpus data. In addition, one of the topic modeling techniques, LDA identified suicide factors by classifying thematic literature, and co-word analysis and visualization were conducted to analyze the factors in-depth.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.1
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• pp.313-332
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• 2009

Cross-language text categorization(CLTC) can classify documents automatically using training set from other language. In this study, collections appropriated for CLTC were extracted from KTSET. Classification performance of various CLTC methods were compared by SVM classifier using machine translation. Results showed that the classification performance in the order of poly-lingual training method, training-set translation and test-set translation. However, training-set translation could be regarded as the most useful method among CLTC, because it was efficient for machine translation and easily adapted to general environment. On the other hand, low performance was shown to be due to the feature reduction or features with no subject characteristics, which occurred in the process of machine translation of CLTC.

• STIMA Bulletin
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• s.2
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• pp.27-45
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• 2005

• Journal of Korean Library and Information Science Society
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• v.42 no.3
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• pp.5-24
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• 2011

The purpose of this study aims to provide possible suggestions for the improvement KDC 5th ed. as a system. After analyzing and evaluating time & space devices of KDC 5th ed.(including DDC 22th ed. and NDC 9th ed.). such as main schedules, common auxiliary tables, internal tables and notes, suggestions for the improvement were proposed. If above suggestions are adopted, effective literature classification scheme which is suited to domestic circumstances will be certainly prepared.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.4
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• pp.181-199
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• 2008

This study presents an empirical study of classification system design focused upon an image design team within an organizational setting. It aims to understand collaboration during design practice. Data was collected through on-site interviews, observations, and document and email reviews. This study uses social process model as a conceptual framework. The study revealed type of collaboration, factors influencing collaboration, influences of collaboration on design practice.