• International Journal of Railway
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• v.2 no.1
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• pp.37-42
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• 2009

Information management of products and services in every industries is gaining importance for resource planning and maintenance. In this paper, we analyzed the information classification systems for railway industry. International and domestic classification systems, such as HS, UNSPSC, eCl@ss and ISIC, are reviewed; as a result this paper presents the findings and the various issues. We proposed to-be images in adopting and utilizing the classification systems. Using the integrative information classification systems could make efficient electronic procurement, supply chain management and e-Business of railway services.

• Journal of Korean Medical classics
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• v.36 no.3
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• pp.89-128
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• 2023

Objectives : This study aims to diachronically examine the classification systems of all materia medica, followed by categorization and analysis of each category to deduce each category's characteristic. This will provide foundation for further examining classifications of bencao in contemporary herbology. Methods : Classification systems from a total of 93 bencao related texts were collected and categorized. Each category's classification system was analyzed to determine its meaning. The classification systems were compared from a diachronic perspective, to further deduce each system's problem from a historical context. Results : The classification systems of materia medica could be summarized as following three standards: quality, origin, and medical application. In reality, bencao could be generally classified according to origin and medical application. The origin-based classification system provided a stable and flexible classification outline in the expansion process of bencao. The medical application-based classification strengthened the relationship between bencao and illness pattern, improving clinical applicability. Conclusions : In the history of herbology, the two classification systems created the current of herbology through mutual contribution and conflict. We hope that further discussion on the direction towards which classification system of bencao in contemporary herbology should head will proceed based on this study.

• International Journal of Knowledge Content Development & Technology
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• v.2 no.1
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• pp.51-65
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• 2012

While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists' research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to achieve interoperability of the information and thus not easy to implement meaningful science technology information services through information convergence. This study aims to address the aforementioned issue by analyzing mapping systems between classification systems in order to design a structure to connect a variety of classification systems used in the academic information database of the Korea Institute of Science and Technology Information, which provides science and technology information portal service. This study also aims to design a mapping system for the classification systems to be applied to actual science and technology information services and information management systems.

• IE interfaces
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• v.18 no.1
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• pp.10-21
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• 2005

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. In this research we compare the performance of Naive Bayesian learning and Centroid-Based Classification using the different data set of an on-line shopping mall and a credit card company. We analyze which method performs better under which conditions. We compared classification accuracy of them which depends on structure and size of train set and increasing numbers of class. The experimental results indicate that Naive Bayesian learning performs better, while Centroid-Based Classification is more robust in terms of classification accuracy.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.376-384
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• 2016

Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.23-41
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• 1995

Business researchers have traditionally used statistical techniques for classification. In late 1980's, inductive learning started to be used for business classification. Recently, neural network began to be a, pp.ied for business classification. This study reviews the business classification studies, identifies a neural network a, pp.oach as the most powerful classification tool, and discusses the problems and issues in neural network a, pp.ications.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.6
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• pp.857-865
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• 1995

The main purposes of this study were to find out the new classification system of the clothing evaluative criteria(CEC), 3nd to clear up the relationshiops of new classification system and the existing classification systems. For this purpose, the existing literatures related with the CEC(the classification system, and the variables) were investigated. The results of the study were as follows: 1. The existing classification systems were 'the intrinsic. non-intrinsic classification', 'the level classification', 'the purchase process classification' The new classification system of the CEC is based on 'the view-point of subjets'. The system was divided into the point of clothing itself, the wearer, the other, the wearing situation. The wearer's point of view is divided into the point of the value, and the physical characteristics of wearer 2. The image was included as the concept of the CEC, and the image classification could be suggested. 3. The relationships of the classification systems were as follows: $\circled1$ The intrinsic. non-intrinsic classification system included the level classification, the view-point classification, the image classification, and the buying process classificstion. $\circled2$ The level classification, the view.point classification, and the image classification were linked mutually, but the buying process classification is seperated from these classifications.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.241-262
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• 2010

This study aims to perform an evaluation of classification systems provided by major Korean search portals, Naver, Nate, Daum, and Yahoo-Korea. These classification systems are evaluated in terms of the consistency of classification system, logicality of classification system, ease of interface, clarity of category names, order of category and site listing, and hierarchical structure. The results of this study show that each search portal provides separate classification systems for their services. These results imply that it is crucial for search portals to implement a common classification system and a common interface for their services. This study could contribute to the development and improvement of portals' classification systems.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.39-45
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• 2022

For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.23-37
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• 2010

Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.