• Proceedings of the Korean Society for Information Management Conference
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• 1994.12a
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• pp.133-136
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• 1994

문헌분류는 지식분류에 입각하여야 한다는 분류의 제 1원리를 규명하기 위하여 지식의 발전과정을 인식론적 관점에서 규명하였으며. 이를 바탕으로 지식분류가 문헌분류에 어떤 영향력을 미쳤는가를 규명하였다. 주제개념은 주관적 관념론, 객관적 관념론, 실용주의, 유물론으로 구분하여 분석하였다. 분석된 결과에 따라 지식분류가 어떤 인식의 관점에서 전개되어 왔는지를 인도의 베다분류법을 비롯하여 플라톤과 아리스토텔레스의 지식분류에서부터 현재의 머시럼, 브리테니카 3의 분류법에 이르기까지 분석하였다. 또한 이를 토대로 지식분류와 문헌분류의 상보성을 규명하였다.

• Journal of Korean Library and Information Science Society
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• v.33 no.1
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• pp.143-167
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• 2002

The aim of this study is to examine the influence of foreign library classification schemes on the Chinese classification systems in the library. And the study is to analyze development process of three modem library classification schemes, the $\ulcorner$Renmin University of China's Library Books Classifications$\lrcorner$, $\ulcorner$Chinese Academy of Sciences's Library Books Classifications$\lrcorner$and $\ulcorner$Chinese Library Classification$\lrcorner$which are being used in many libraries in China where the library is regarded an important organization for performing the national policies.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.25-50
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• 2021

General-purpose classification scheme encompasses all subject areas, While the whole classification scheme is constructed by library studies experts, structure and preparation of each specific subject area's classification should be referenced to that specific subject. In order for the whole system to be practical and useful classification scheme, not just a simple collection of each subject area's scheme, it is necessary to set the rule for properly distributing the amount of classification items, and the collections assigned to these items. The rule to set the distribution of items based on the amount of document collections is called 'literary warrant'. This study examines actual status of assignment of each classification items to information resources, as a result of application of Korean Decimal Classification, and then suggests a way to improve these practices.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.251-271
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• 2007

This paper studies the problem of classifying documents with labeled and unlabeled learning data, especially with regards to using document similarity features. The problem of using unlabeled data is practically important because in many information systems obtaining training labels is expensive, while large quantities of unlabeled documents are readily available. There are two steps In general semi-supervised learning algorithm. First, it trains a classifier using the available labeled documents, and classifies the unlabeled documents. Then, it trains a new classifier using all the training documents which were labeled either manually or automatically. We suggested two types of semi-supervised learning algorithm with regards to using document similarity features. The one is one step semi-supervised learning which is using unlabeled documents only to generate document similarity features. And the other is two step semi-supervised learning which is using unlabeled documents as learning examples as well as similarity features. Experimental results, obtained using support vector machines and naive Bayes classifier, show that we can get improved performance with small labeled and large unlabeled documents then the performance of supervised learning which uses labeled-only data. When considering the efficiency of a classifier system, the one step semi-supervised learning algorithm which is suggested in this study could be a good solution for improving classification performance with unlabeled documents.

• Proceedings of the Korean Society for Information Management Conference
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• 1997.08a
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• pp.95-98
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• 1997

의학사 연구영역의 확대로 다양한 주제를 다룬 연구문헌들이 배출되고 있음에도 불구하고 분류표에서 의학사는 매우 간단하게 취급되고 있어 이들 문헌을 분류하는데 어려움이 있다. 본 연구에서는 KDC, DDC, 중국도서관 도서분류법 등 일반 도서관용 분류표와 NLMC, 보스톤의학도서관분류,. 커닝햄분류표, 버나드분류표 등 의학도서관용 분류표에서 의학사가 어떻게 취급되고 있는 지 살펴보았으며, 의학사문헌의 보다 정확한 분류 및 분류표 재전개를 위하여 의학사의 연구범주를 고찰하였다.

• 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.39 no.3
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• pp.369-386
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• 2008

The purpose of this study is investigate to compare with knowledge classification and library classification system of botany. First, the knowledge field of botany is mainly classified in morphology, physiology, ecology, taxonomy, genetics, evolution and others by the study object of plants. Second, the division of plants is treated in the field of taxonomy, that is, a lower subdivision study of botany, and Engler's classification is still prevalent in the taxonomy. Third, in library classification, KDC, NDC, UDC and CC adopted the Engler's classification, but DDC and LCC was taken of the Bentham & Hooker's classification. In the Engler's classification, plants are arranged by evolution's order, from lower vegetation to higher vegetation, but Bentham & Hooker's classification is arranged in the reverse order. Forth, it is desirable that every plants(482-489) of KDC' botany are subdivided by the attribute or structure of plants being treated in the general botany as if they are subdivided in the DDC or CC.

• Proceedings of the Korean Society for Information Management Conference
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• 1994.12a
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• pp.125-128
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• 1994

본 연구는 한국도서관학관계문헌색인, 1945-1974와 한국문헌정보학 색인, 1975-1992를 바탕으로 해방 후 48년간의 한국 분류학계가 어떻게 이루어져 왔는지를 연구해 보았다. 이병수, 임종순, 천혜봉, 배영활, 이경호 등에 의해 많은 문헌이 발표되었으며 국립중앙도서관의 도서관에 가장 많은 관련 문헌이 발표되었다. 1970년대 중반 이후로는 대학 논집과 전공학과의 학보에도 많은 문헌이 발행되기 시작하였다. 많은 발전에도 불구하고 외국과 비교해 보면 분류만을 중점적으로 연구하는 연구 단체의 조성과 그 단체가 주축으로 만들어지는 분류 전문 학술지의 발행이 시급하다.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.261-287
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• 2005

The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.1
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• pp.39-57
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• 2006

Cadastral Science has not been evaluated as an independent discipline according to Code of Research Fields of Korea Research Foundation. The purpose of this study is to find the problems of knowledge classification of Cadastral Science and suggest method of improvement. For the studying, analyzes the definition, objects of research, educational system and curriculum of Cadastral Science. Besides, investigates the condition of Cadastre classification on Code of Research Fields, DDC and KDC. This paper suggests that Cadastral Science can be restructured to the new Interdisciplinary Studies and moved to the upper division. The items of division and subdivision can be also added.