• Journal of the Korean Society for Library and Information Science
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• v.50 no.3
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• pp.249-265
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• 2016

The objective of this study is to analyze the characteristics of Cutter's Expansive Classification. The four elements about classification evaluation were applied to analyze it. Results show that first, from philosophy and religion class to literature class, the order of main classes is logical and evolutionary. Second, the notation is a pure notation including author mark. Third, the classification is expansive from first classification to seventh classification. Science classes were expanded in the second classification comparing to the first classification. From the third classification, all classes were expanded. Fourth, it was applied by the local list to indicate places emphasizing connection of geographical space.

• Journal of Korean Library and Information Science Society
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• v.35 no.3
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• pp.293-319
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• 2004

This study reviews classification used the Chosun Government-General Library which library was the first of a government library in the Korea Chosun Government-General Library made and used the Eastern Books Classification, Old Books Classification and foreign Books Classification. This study investigates the characteristics of the Chosun Government-General Library Classification which library was a government library at the time of Japanese occupation of Korea. This study also compares and analyzes the classification with other major related classification system at that time to identify the relationship of influence among them.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.9-17
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• 2011

For the exact status of the land such as land cover classification and land use classification, feature classification system has been utilized in several organizations and agencies. However, those classification systems are limited to detection of land change and it's also not suited for the extraction of land changed. In this study, we would proposed a standard feature classification system which presents both in natural and artificial change of land effectively. Based on comparison and analysis of domestic and foreign relevant feature classification system, we proposed a standard feature classification system. In order to validate the applicability of the proposed feature classification system, we evaluated the accuracy with using automatic feature classification based on supervised classification and pre-knowledge hierarchical classification.

• Journal of Korean Library and Information Science Society
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• v.35 no.2
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• pp.135-154
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• 2004

This study was investigated to the geographical categories and arrangement of library classifications and public organizations in ender to understand the geographical category comprehension and canon from the north-west to south-east in Korean library classification and then to develop a Korean geographical classification system Research method was the examination of different type of library classification (DDC, NDC, LCC) and geographical categorizations of the public organizations. The results show that there was not a principle of categorization and arrangement for geographical information. This study proposes to the three hierarchical structures and radial category arrangement from center-area to side area for developing Km geographical classification.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.2
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• pp.287-304
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• 2016

This study examines the influence of product classification standards and structure on user perception as well as their attitude towards online shopping sites. The causal relationships of variables are also examined. The analysis was based on an online survey with 247 responses. Four types of internet shopping sites were developed and used as a stimulus. The results of the mean comparison analysis indicated that perceived variety, information overload, perceived shopping value and attitude towards the site varies significantly with product classification standards and structure. There was also of a marginally significant interaction between the classification standard and structure on perceived variety and information overload. The causal relationship analysis revealed that perceived variety positively influenced hedonic and utilitarian shopping value. However, information overload had a negative effect on hedonic and utilitarian shopping value. Both the hedonic and utilitarian shopping value positively influenced attitudes towards the sites. This study demonstrates that classification method influences customer perception and attitude. It offers interesting insights on a product classification method as a strategic tool for online shopping.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.197-219
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• 2009

The study acknowledges the need for classification systems in arts and cultural education. The study constructs a faceted classification system for this domain based on systematic methods. The study utilized iterative collaboration between domain experts and classification system developers. The classification system consists of 13 main facets and terms. The classification system has values to manage information resources effectively and efficiently. It is also beneficial for reducing cultural gaps in arts and cultural education as well as providing an information gateway for users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.229-232
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• 2008

A Neural network classification of human activity data is presented. The data acquisition system involves a tri-axial accelerometer in wireless sensor network environment. The wireless ad-hoc system has the advantage of small size, convenience for wearability and cost effectiveness. The system can further improve the range of user mobility with the inclusion of ad-hoc environment. The classification is based on the frequencies of the involved activities. The most significant Fast Fourier coefficients, of the acceleration of the body movement, are used for classification of the daily activities like, Rest walk and Run. A supervised learning approach is used. The work presents classification accuracy with the available fast batch training algorithms i.e. Levenberg-Marquardt and Resilient back propagation scheme is used for training and calculation of accuracy.

• The Journal of Korean Medical History
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• v.19 no.1
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• pp.65-76
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• 2006

The present study examined subject classification and the characteristics of old Oriental medicine literature focused on Web services of Oriental medicine knowledge and information resources. For this, we reviewed how subject classification is applied to Oriental medicine in the codified literature classification table and, based on the results, examined how the classification system is used in libraries. Second, subject classification and the characteristics of old Oriental medicine literature were studied focused on Web services of Oriental medicine knowledge and information resources, and related problems and solutions were suggested.

• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.10-26
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• 2013

Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.