• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.265-268
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• 2001

As growing the electronic commerce there are significant changes in the products/services catalog into the on-line environment. Advertent of e-catalog business opportunity for their own product/services enlarges the market volume and there are diverse methods for the presentation of its product/services. A method for the presentation of product/services features one uses identification and classification system. This study constructs a classification system and database layout for the product/services classification system as a part of e-catalog system. We consider the specific method for the GDAS-based dataset and UNSPSC classification system in the distribution industry.

• Journal of Korea Technology Innovation Society
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• v.10 no.3
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• pp.531-554
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• 2007

This paper suggests a new model connecting various knowledge activities through classification systems such as classifications of research, technology, industry, major and job. Although research activities are linked to technology and industry areas or to education and job areas, there is no effort to link these kinds of activities. There are a few studies to link research and technology or research and education respectively. But, there have been no studies to connect technology-industry linkage and education-job linkage. This paper suggests that research area can be a basis of link between technology-industry linkage and education-job linkage. The methods building the links are not simple, but easy; 1) setting up new science/research classification system having two dimensions of research and application, 2) building electronic systems and databases allowing fields for several classification systems, and 3) making rules using multi-dimensional classification systems following the purpose of the programs. The model is designed to meet the needs of nationwide R&D and human resources policies, and for the preparation of knowledge society to grasp the relationship between sequential activities using knowledge. If we know the interactive relationships between various areas, we can trace related phenomena in different activities with restricted information.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.79-95
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• 2024

In modern society, as data plays a crucial role at the levels of businesses, industries, and nations, the utilization of data becomes increasingly important. Consequently, governments are prioritizing the development and implementation of plans to cultivate data workforce, viewing the data industry as a cornerstone of national strategy. To enhance domestic capabilities and nurture workforce in the data industry, it is deemed necessary to conduct an objective comparative analysis with major foreign countries. Therefore, this study aims to analyze cases of domestic and international data industries and explore methods for quantitatively comparing data industry workforce across nations. Initially, the study distinguishes between "data industry workforce" and "data job-related workforce," particularly focusing on professionals handling data-related tasks. Subsequently, it compares the workforce sizes of data job-related workforce across nations, utilizing standardized occupational classification codes based on the International Standard Classification of Occupations(ISCO). However, it should be noted that countries employing their own unique occupational classification systems often require matching job titles with similar meanings for accurate comparison. Through this study, it is anticipated that policymakers will be able to establish future directions for cultivating data workforce based on comparable status.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.215-225
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• 2024

With the rapid development of Internet of Things (IoT) and big data technology, a large amount of data will be generated during the operation of related industries. How to classify the generated data accurately has become the core of research on data mining and processing in IoT industry chain. This study constructs a classification model of IoT industry chain based on improved random forest algorithm and text analysis, aiming to achieve efficient and accurate classification of IoT industry chain big data by improving traditional algorithms. The accuracy, precision, recall, and AUC value size of the traditional Random Forest algorithm and the algorithm used in the paper are compared on different datasets. The experimental results show that the algorithm model used in this paper has better performance on different datasets, and the accuracy and recall performance on four datasets are better than the traditional algorithm, and the accuracy performance on two datasets, P-I Diabetes and Loan Default, is better than the random forest model, and its final data classification results are better. Through the construction of this model, we can accurately classify the massive data generated in the IoT industry chain, thus providing more research value for the data mining and processing technology of the IoT industry chain.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.181-182
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• 2015

Lately, the importance of the marin industry is growing as current status and future trend. This change is being prompted for the development of the maritime industry such as resource depletion, climate change, the Arctic opens. The demand of new marine industry with IT and convergence is gradually increasing. A new understanding of the importance of the marine industry is needed. Therefore, the systematic classification system for the marin industry building for the marin industry is to assess the marine industry activity levels at the national level.

• Journal of Radiation Industry
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• v.8 no.3
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• pp.155-159
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• 2014

RI-Biomics is a new concept that combines radioisotopes (RI) and Biomics. For efficient collection of information, establishment of database for technical information system and its application to the system, there is an increasing need for constructing the standard classification system of technical information by its systematical classification. In this paper, we have summarized the development process of the standard classification system of technical information in the field of RI-Biomics and its application to the system. Constructing the draft version for the standard classification system of technical information was based on that standard classification one in national science and technology in Korea. The final classification system was then derived through the reconstruction and the feedback process based on the consultation from the 7 experts. These results were applied to the database of technical information system after transforming as standard code. Thus, the standard classification system were composed of 5 large classifications and 20 small classifications, and those classification are expected to establish the foundation of information system by achieving the circular structure of collection-analysis-application of information.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.103-117
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• 2023

This study focuses on the behavioural lexical classification for extracting animation character actions and the analysis of the character's upper and lower body movements. The behaviour and state of characters in the animation industry are crucial, and digital technology is enhancing the industry's value. However, research on animation motion application technology and behavioural lexical classification is still lacking. Therefore, this study aims to classify the predicates enabling animation motion, differentiate the upper and lower body movements of characters, and apply the behavioural lexicon's motion data. The necessity of this research lies in the potential contributions of advanced character motion technology to various industrial fields, and the use of the behavioural lexicon to elucidate and repurpose character motion. The research method applies a grammatical, behavioural, and semantic predicate classification and behavioural motion analysis based on the character's upper and lower body movements.

• Korea Journal of Hospital Management
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• v.21 no.4
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• pp.55-62
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• 2016

Purposes: The industry has specialized and fragmented than in the past. As a factor of economic growth and industrialization, the number of people employed in primary industry decreased and the number of people employed in secondary and third industry continuously increased. In modern times, incidence of chronic disease is increasing according to industrial development. So, the purpose of this study was to analyze the chronic disease according to Clark's industrial classification. Methodology: Data were derived from the 2012 Korea Health Panel. The sample was made up of 7,132 adult participants aged 20 or over selected Korea Health Panel by probability sampling from Korea. Binary logistic regression analysis was conducted to examine the main factors associated with chronic disease. Findings: The significant factors associated with chronic disease were gender, age, marital status, household member, education level, insurance type, disability, BMI, and industrial classification. Female, elderly, divorced(including bereavement, missing and separation), one-person households, less than high school graduation, medical aid, disability, obese and primary industry were confirmed chronic disease increases. Practical Implications: The study finds that primary industry's prevalence of chronic disease was higher than secondary and third industry. Therefore, this study aims to management and effort of the worker who engaged in the primary industry. Policy development is required to address inequality or popularization of the differences in these factors by conducting a study to define the working conditions and socio-economic factors between industry.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.497-506
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• 2022

In recent years, the specialized construction industry has undergone major construction and major industries, and without considering the technical expertise of construction works, the construction industry is promoting the integration and establishment of specialized construction industries according to convenience and abolition of their own industries. As the reorganization plan causes confusion in the production structure and lacks persuasive power by aiming only for industry simplification, it is judged to be desirable to review it according to the detailed characteristics of the specialized construction industry. In this study, -to review the reorganization of a rational classification system that considers the specific nature of the specialization of specialized construction projects, the classification of construction works, major work contents and characteristics, technical expertise, and problems of largescale industry in the case of painting construction and landscaping construction was analyzed. Based on this, aspects to be considered when reorganizing the current professional construction industry classification system are identified and reasonable improvement plans for each industry are suggested.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.23-30
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• 2021

An Automated Industry and Occupation Coding System assigns statistical classification code to the enormous amount of natural language data collected from people who write about their industry and occupation. Unlike previous studies that applied information retrieval, we propose a system that does not need an index database and gives proper code regardless of the level of classification. Also, we show our model, which utilized KoBERT that achieves high performance in natural language downstream tasks with deep learning, outperforms baseline. Our method achieves 95.65%, 91.51%, and 97.66% in Occupation/Industry Code Classification of Population and Housing Census, and Industry Code Classification of Census on Basic Characteristics of Establishments. Moreover, we also demonstrate future improvements through error analysis in the respect of data and modeling.