• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.1
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• pp.115-136
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• 2020

It is necessary to find a genre classification by reflecting the needs of users since a subject that makes up the highest proportion of books in the school library is fictions in literature and KDC cannot accept user's need to access fiction in school libraries. This study suggested the genre classification for fictions in school libraries through surveying classification of fictions in domestic and foreign libraries, and comparing between classification systems of online/offline bookstores, KDC and DDC. For developing the genre classification system, it is to collect genre terms for fictions, to extract 14 genre headings among them, and to assign the acronym of English genre terms as classification notation. For applying the newly developed genre classification, KDC number of one middle school library was converted as the 3 methods such as combination of KDC, genre term before 800 and only genre terms. This study could contribute to suggest the genre classification of fiction to reflect user needs and to overcome the limitation of hierachical classification in KDC.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.269-288
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• 2024

To structure the KOS registry, it is necessary to select a classification system that suits the characteristics of the collected KOS. This study aimed to classify domestic KOS collected through various classification schems, and based on these results, provide insights for selecting a classification system when structuring the KOS registry. A total of 313 KOS data collected via web searches were categorized using five types of classification systems and a thesaurus, and the results were analyzed. The analysis indicated that for international linkage of the KOS registry, foreign classification systems should be applied, and for optimization with domestic knowledge resources or to cater to domestic researchers, domestic classification systems need to be applied. Additionally, depending on the field-specific characteristics of the KOS, research area KOS should apply classification systems based on academic disciplines, while public sector KOS should consider classification systems based on government functions. Lastly, it is necessary to strengthen the linkage between domestic and international KOS, which also requires the application of multiple classification systems.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.4
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• pp.1-7
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• 2001

Remotely sensed data is the most fundamental data in acquiring the GIS informations, and may be analyzed to extract useful thematic information. Multi-spectral classification is one of the most often used methods of information extraction. The actual multi-spectral classification may be performed using either supervised or unsupervised approaches. This paper analyze the effect of assigning clever initial values to image classes on the performance of parallelepiped classification algorithm, which is one of the supervised classification algorithms. First, we investigate the effect on serial computing model, then expand it on MIMD(Multiple Instruction Multiple Data) parallel computing model. On serial computing model, the performance of the parallel pipe algorithm improved 2.4 times at most and, on MIMD parallel computing model the performance improved about 2.5 times as clever initial values are assigned to image class. Through computer simulation we find that initial values of image class greatly affect the performance of parallelepiped classification algorithms, and it can be improved greatly when classes on both serial computing model and MIMD parallel computation model.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.178-186
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• 2018

Subject classification of thesis units is essential to serve scholarly information deliverables. However, to date, there is a journal-based topic classification, and there are not many article-level subject classification services. In the case of academic papers among domestic works, subject classification can be a more important information because it can cover a larger area of service and can provide service by setting a range. However, the problem of classifying themes by field requires the hands of experts in various fields, and various methods of verification are needed to increase accuracy. In this paper, we try to classify topics using the unsupervised learning algorithm to find the correct answer in the unknown state and compare the results of the subject classification algorithms using the coherence and perplexity. The unsupervised learning algorithms are a well-known Hierarchical Dirichlet Process (HDP), Latent Dirichlet Allocation (LDA) and Latent Semantic Indexing (LSI) algorithm.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.213-219
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• 2020

In this paper, we propose a classification analysis method for diagnosing and predicting problematic smartphone use in order to provide policy data on problematic smartphone use, which is getting worse year after year. Attempts have been made to identify key variables that affect the study. For this purpose, the classification rates of Decision Tree, Random Forest, and Support Vector Machine among machine learning analysis methods, which are artificial intelligence methods, were compared. The data were from 25,465 people who responded to the '2018 Problematic Smartphone Use Survey' provided by the Korea Information Society Agency and analyzed using the R statistical package (ver. 3.6.2). As a result, the three classification techniques showed similar classification rates, and there was no problem of overfitting the model. The classification rate of the Support Vector Machine was the highest among the three classification methods, followed by Decision Tree and Random Forest. The top three variables affecting the classification rate among smartphone use types were Life Service type, Information Seeking type, and Leisure Activity Seeking type.

• Journal of Information Management
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• v.43 no.1
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• pp.41-62
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• 2012

Because of the electronic commerce development, share of the internet bookstore is rising every year in the publication circulation market. Also, the book search in the internet bookstore may smarten more forward according to development trend of the electronic book, and importance of the classification system of the internet bookstore is expected that also rise continuously. The purpose of this study is to offer the classification system that can search the social science books of the internet bookstore efficiently. For this study, compared and analyzed the classification system of internal and external 10 internet bookstores. This study may be used to other subject study of the internet bookstore, and it expect to is used to basic data for the classification system of the internet bookstore in the future.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.201-215
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• 2015

Recently advanced security threats have increasingly occurred, and the necessity and importance of Information Security has been growing with the advent of the era of convergence beyond information-oriented age. Most domestic studies in the field of occupational classification of Information Security have only focused on technology-oriented occupations. Relatively little research has been carried out on the occupational classification in the view of convergence environment. Therefore, in this paper we gave a definition of Information Security occupations, classified them and draw required capabilities by occupations in order to design the occupational classification system of Information Security and the required capabilities for future convergence environment by analyzing the previous studies. We also reclassified the occupational classification and required capabilities by occupations, and verified the validity of them based on National Initiative for Cybersecurity Education's the occupational classification system of Information Security considering the future convertgence environment. It is expected that the results of this study will be employed as base data for manpower demand and supply and improvement of working conditions in the future convergence environments. In the future study we will build standardized instruction methods which provide occupational capabilities by using the required capabilities by occupations.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.81-88
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• 2015

Recently the Security fields is emerged as a important issue in the world, While a variety of techniques such as a Cloud Computing or a Internet Of Things appeared. In these circumstances, The domestic security fields are divided into the Information Security, the Physical Security and the Convergence Security. and among these security fields, Convergence security is attracted much attention from various industries. the classification systems of a new field Convergence Security has become a very important criteria such about the Statistics calculation, the Analysis of status industry sector and the Road maps. However, In the domestic, The related institutions classified each other differently the Convergence Security Classification. so it is urgently needed a domestic security fields systematic classification due to the problems such as lack of reliability of the accuracy, compatibility of a data. Therefore, this paper will be analyzed to the characteristics of the domestic security classification systems by the cases. and will be proposed the newly improved classification system, to be possible to addition or deletion of an classification entries, and to be easy expanded according to the new technology trends. this proposed to classification system is expected to be utilized as a basis for the construct of a domestic security classification system in a future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.376-379
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• 2003

In this paper we describe DCClass, a tool for fuzzy information granulation with transparency constraints. The tool is particularly suited to solve fuzzy classification problems, since it is able to automatically extract information granules with class labels. For transparency pursuits, the resulting information granules are represented in form of fuzzy Cartesian product of one-dimensional fuzzy sets. As a key feature, the proposed tool is capable to self-determining the optimal granularity level of each one-dimensional fuzzy set by exploiting class information. The resulting fun information granules can be directly translated in human-comprehensible fuzzy rules to be used for class inference. The paper reports preliminary experimental results on a medical diagnosis problem that shows the utility of the proposed tool.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.81-88
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• 2017

In this paper, we classified the weaknesses of C/C++ programs listed in CWE based on the diagnostic information produced at each stage of program compilation. Our classification identifies which stages should be responsible for analyzing the weaknesses. We also present algorithmic frameworks for detecting typical weaknesses belonging to the classes to demonstrate validness of our scheme. For the weaknesses that cannot be analyzed by using the diagnostic information, we separated them as a group that are often detectable by the analyses that simulate program execution, for instance, symbolic execution and abstract interpretation. We expect that classification of weaknesses, and diagnostic information accordingly, would contribute to systematic development of static analyzers that minimizes false positives and negatives.