• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.1023-1026
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• 2013

오늘날 인터넷의 발달과 더불어 스마트기기의 보급이 급성장하면서, 다양한 웹사이트에서 데이터가 기하급수적으로 발생되고 있고, 수 많은 다종다양한 데이터를 효율적으로 저장/관리/분석하기 위한 유용한 어노테이션(Anotation) 기법으로서, 리소스에 대한 사용자의 태깅(Tagging)기능이 널리 활용되고 있다. 본 연구에서는, 사용자들의 공통 태그 데이터를 수집하여, WordNet을 기반으로 다양한 수준의 태그/사용자 분류체계를 구축하기 위한 지원도구개발에 관한 연구결과를 보고한다.

• Archives of design research
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• v.12 no.4
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• pp.283-292
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• 1999

As network and multimedia service has increased in educational environment, it is needed to study on digital system based educational scenarios, especially in art and design departments in which visual educational materials mainly used. Therefore, this study was conducted with three objectives: first, developing components of design database and their classification system, second, developing contents of database for fundamental form education in design, and third, developing application method of database. According to these objectives, the secondary research was implemented into two directions; the analysis of classification categories of design, and the analysis of contents and process of fundamental form design education. From the secondary research, it was found that design database should have a flexible structure with flexible components as well as fixed components to include subjective and aesthetic assessment. In the end, the application methods and user interface system of design database was developed based on design educational scenarios.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.149-161
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• 2013

In this paper, we propose a novel approach to construction of classification hierarchies for user tags of folksonomies, using WordNet-based Formal Concept Analysis tool, called TagLighter, which is developed on this research. Finally, to give evidence of the usefulness of this approach in practice, we describe some experiments on user tag data of Bibsonomy.org site. The classification hierarchies of user tags constructed by our approach allow us to gain a better and further understanding and insight in tagged data during information retrieval and data analysis on the folksonomy-based systems. We expect that the proposed approach can be used in the fields of web data mining for folksonomy-based web services, social networking systems and semantic web applications.

• Archives of design research
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• v.17 no.3
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• pp.71-80
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• 2004

The culture industrial design classification is the major factor to develop the various potential abilities, promote a new value to change and maximize the competitiveness of industry and the nation. Accordingly it is important to comprehensively understand and recognize the changing of this new design paradigm with its structural contents. In order to have universality data need to be made a classification system in advance for the policy, strategy, analysis indicator and assessing the culture industrial design classification. This study build CIDC that structure divided into three sections(A,B,C) with divisions(medium), classes(small) and groups(specific field) of numeric code from "01" or "001" and increasing their numbers. CIDC is set up in order to search for differences and referential character through comparisons with design-related classification systems as well as making a role of the basic under data for this field.c under data for this field.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.309-319
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• 2007

Right comprehension of the natural disaster could reduce the damage of human life and property by explaining the cause of the disaster and considering a counterplan to decrease or prevent it. To do this, it should precede to clarify the category of the natural disaster and classification. Also, when the disaster occurs, swift site survey and the establishment of the data by the professionals should be done for clarifying the reason. Our classification of the natural disaster is written on the Law of the Nature Disaster Relief. But, this classification is made for the management of the disaster, so it is required to review the establishment of the technical information by the professionals. Therefore, the Korean type classification is required considered by the professionals who collect and study the information of the natural disaster for the other countries. If the DB of the natural disaster is made, it is able to get various services through the internet virtual space and it will be helpful to prepare the prevent countermeasures against the disaster. In this research, the korean type classification plan of the natural disaster is suggested which is suitable to the professional technology by collecting and analyzing the domestic and the international classification of the natural disaster.

• Journal of Korean Academy of Nursing
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• v.31 no.3
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• pp.401-416
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• 2001

현재의 보건의료체계에서는 모든 것이 급박하게 변화하고 있으며 또 구체적인 자료를 요구한다. 컴퓨터의 보급과 함께 이러한 변화에 능동적으로 대처하기 위해 간호학에서도 표준화된 대규모 데이터베이스의 개발이 필수적이다. Nursing Minimum Data Set (NMDS)은 간호학분야에서 개발된 최초의 표준화된 대규모 데이터 베이스로서, 간호가 일어나는 모든 상황에서 반드시 수집되어야 할 핵심적인 간호요소를 포함하고 있다. 따라서 본 논문에서는 NMDS 개발의 역사적인 배경, 목적, 요소, 그리고 간호계의 세계적인 동향과 관련하여 NMDS가 이루어야 할 방향, 그리고 NMDS를 완성하기 위해 선행되어 할 문제로 표준화된 분류체계에 대해 논의하였다. 그리고 미국이외에도 몇몇나라에서 NNDS나 혹은 유사한 데이터베이스가 개발 중이거나 이미 수집되고 있는 나라들이 있으므로 이들에 대한 비교와 분석도 제시하였다. 그리고 보다 최근에 개발된 데이터 베이스로 주로 행정적인 목적을 위해 개발된 Nursing Management Minimum Data Set (NMMDS)을 소개하였다. 즉 NMDS가 임상적인 자료의 수집에 초점을 맞춘 데 비해, NMMD는 효과적인 간호관리에 필수적인 요소들을 포함시켰다. 그래서 간호행정가들이 의사결정에 필요한 재정적자원, 환경적자원, 간호자원에 대한 정보를 수집할 수 있게 고안되었다. 이러한 데이터 베이스들은 관계형 데이터베이스로 서로 연결되어야 하며, 다른 학문분야와도 연계되어 활용되어져야 할 것이다. 만약 이러한 대규모 데이터베이스 들이 한국에서도 개발되고 사용되어 진다면 환자간호에 더욱 비용 효과적인 관리가 가능하게 될 것이다. 마지막으로 우리나라에서 NMDS나 NMMDS 같은 대규모데이터 베이스의 개발이 시급히 요청됨을 강조하였다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.21-30
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• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.848-849
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• 2014

실시간으로 고객의 피드백을 파악할 수 있는 방법으로 SNS 등과 같은 빅 데이터를 이용하는 것이 매우 효율적 이다. 따라서 최근 기업들은 온라인상의 빅 데이터 평판을 분석하는 시스템들을 이용하여 고객피드백에 관한 정보를 수집하고 분석하고 있다. 본 논문에서는 온라인상의 고객피드백의 보다 정확하고 효율적인 정보 수집과 분석이 가능하며 분석 지식체계의 근간을 이루는 서비스 모델구축 방법을 제안한다. 서비스 모델 구축방법은 서비스 산업군에 대한 시소러스 분석 체계를 정의하고 데스트베드 대상의 인터뷰 등을 통하여 분류체계 기본 방향을 수립하며 타겟 대상의 특화된 수집원 및 범위를 설정하는 방법 등으로 이루어진다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.