• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.171-191
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• 2004

This study presents revision scheme of Korean Decimal Classification appropriate for classification of children-related materials, mainly centered on social science(300) and pure science(400) occupying the majority of children-related materials in school Libraries. Towards this goal, 1 have studied the development and use of classification system for children-related materials available in domestic and overseas school libraries or children's libraries, and researched elementary school 4th, 5th, and 6th grade students' degree of understanding on classification item terms and children-related materials terms used for KDC's social science and Pure science. Based on the results of analysis, f have presented revision scheme of Korean Decimal Classification item terms and class numbers for children-related materials.

• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.127-130
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• 2014

이 연구에서는 도서관의 주요 장서에 해당하는 단행본 도서에 대한 자동 분류를 적용가능한지 알아보고자 하였다. 분류자질로 메타데이터인 서명, 목차, 책 소개를 사용하였으며, 다양한 자질 가중치를 적용하여 581건의 단행본 도서를 통해 kNN 분류기의 분류성능을 파악하였다. 실험 결과 이들 메타데이터를 모두 사용하였을 때 가장 좋은 분류성능을 가져왔으며, 실험문헌집단의 규모가 작은 한계가 있지만 로그 TF를 취한 가중치 방법이 좋은 성능을 가져왔다.

• Journal of Korean Library and Information Science Society
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• v.31 no.4
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• pp.111-138
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• 2000

The lxnpose of this study is to pmvide the basic data for developing rational classification scheme of intemet resources in the fields of the information & telecommunications technology. The coverage of this study is, kt, to dehe the concept of informtion & telecommunications, and also to investigate the division of information & telecommunications technology through the literature, seumd, to analyze the using library classification schemes for internet resources, and thud, to review classi6cation system of the directory search engines. In this study, I w new

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.63-88
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• 2018

This research evaluated differences of classification performance for feature selection methods using LDA topic model and Doc2Vec which is based on word embedding using deep learning, feature corpus sizes and classification algorithms. In addition to find the feature corpus with high performance of classification, an experiment was conducted using feature corpus was composed differently according to the location of the document and by adjusting the size of the feature corpus. Conclusionally, in the experiments using deep learning evaluate training frequency and specifically considered information for context inference. This study constructed biomedical document dataset, Disease-35083 which consisted biomedical scholarly documents provided by PMC and categorized by the disease category. Throughout the study this research verifies which type and size of feature corpus produces the highest performance and, also suggests some feature corpus which carry an extensibility to specific feature by displaying efficiency during the training time. Additionally, this research compares the differences between deep learning and existing method and suggests an appropriate method by classification environment.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.295-312
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• 2019

This study was conducted with a view to investigating and analyzing classification and types of literature sources of Sikuquanshuzongmutiyao and the results of this study are as follows. First, the literature sources of Sikuquanshuzongmutiyao were classified mainly into five types including national version, provincial version, individual version, public official version, and societal distribution version. Second, court and Emperor's version was classified as national version, while literatures collected from state and province were classified as provincial version. Third, each of individual version and public official version, which were not clearly differentiated from each other due to their being named private version, were distinctively and separately classified. They were classified into individual version if associated by province name and book owners' names and into public official version if associated by public post names and public official's name. Fourth, societal distribution version included distributed and purchased versions in the society of those days. Fifth, in terms of the number of literature listed in all descriptions of Sikuquanshu, provincial version, national version, individual version, public official version, and societal distribution version were more found in the descending order. Sixth, it was found out that causes are being a little more stressed in the description of reference names of Sikuquanshuzongmutiyao through 1) public post names on public official version, 2) company names on private version, and 3) names of societal distribution version instead of sales version.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.3
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• pp.127-144
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• 2007

The purpose of this study is to design the classification system for christian information resources on the internet in Korea. For this purpose, the study is investigated the divisions of Christianity of (1) library classifications: KDC, DDC, LCC, (2) portal sites: Daum, Empas, Naver, (3) Christianity Portal sites GodPeaple, Kidok, Godpia. And it compared the classification systems of KDC, DDC and GodPeaple. This study selected criteria as follows: comprehension, logicality, definiteness, efficiency and current topics. It suggested the classification system(draft) for christian information resources on internet which are composed of 10 classes.

• Journal of Korean Library and Information Science Society
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• v.37 no.1
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• pp.329-352
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• 2006

This study investigated the background of the first and revised editions of the Han-Un Decimal Classification(HUDC), and analyzed their relationships to and influences on other major related classification systems. HUDC was compiled in 1954 and revised in 1981. HUDC was influenced by NDC in most classes of main classes and mnemonic schedules, and influenced by KDCP in the classes Religion, Language and Literature.

• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.205-224
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• 2012

One of the limitations of BOW method is that each term is recognized only by its form, failing to represent the term's meaning or thematic background. To overcome the limitation, different profiles for each term were defined by thematic categories depending on contextual characteristics. In this study, a specific term was used as a classification feature based on its meaning or thematic background through the process of comparing the context in those profiles with the occurrences in an actual document. The experiment was conducted in three phases; term weighting, ensemble classifier implementation, and feature selection. The classification performance was enhanced in all the phases with the ensemble classifier showing the highest performance score. Also, the outcome showed that the proposed method was effective in reducing the performance bias caused by the total number of learning documents.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.1-21
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• 2023

This study specifically reviewed the performance of the ranking schemes as an efficient feature selection method for text classification. Until now, feature ranking schemes are mostly based on document frequency, and relatively few cases have used the term frequency. Therefore, the performance of single ranking metrics using term frequency and document frequency individually was examined as a feature selection method for text classification, and then the performance of combination ranking schemes using both was reviewed. Specifically, a classification experiment was conducted in an environment using two data sets (Reuters-21578, 20NG) and five classifiers (SVM, NB, ROC, TRA, RNN), and to secure the reliability of the results, 5-Fold cross-validation and t-test were applied. As a result, as a single ranking scheme, the document frequency-based single ranking metric (chi) showed good performance overall. In addition, it was found that there was no significant difference between the highest-performance single ranking and the combination ranking schemes. Therefore, in an environment where sufficient learning documents can be secured in text classification, it is more efficient to use a single ranking metric (chi) based on document frequency as a feature selection method.

• Journal of Korean Library and Information Science Society
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• v.44 no.2
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• pp.399-422
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• 2013

This study suggests some ideas for improvement of mixing classification and illogical subdivisions arrangement of Statistics in Social Science and Mathematical Statistics in Natural Science on KDC. We investigate the characteristics, educational system, and curriculum of Statistics in Korea. Besides, we compare and analyze classification systems such as KDC, DDC, LCC, NDC and Research Fields Code by National Research Foundation of Korea. As a result, Statistics in Social Science is relocated and integrated with the subfield of Natural Science according to the academic background. Existing social statistics topics are subdivided into statistical research methods complementing social science research methods. The heading 'Probabilities, Statistical mathematics' in Natural Science is changed to 'Statistics', and the subdivisions are expanded and revised.