• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.477-479
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• 2022

본 논문에서는 기업 비즈니스 분석을 위해 한국표준산업분류에 근거하여 국내 사업체의 산업군을 분류하는 앙상블 분류 모델 구축 방법론을 제시한다. 기업 평가 및 보고서 자동화 시스템 구축을 위해 기업의 재무제표 정보, 기업등록부와 같은 신고 정보, 사업체 조사 정보에 포함된 텍스트 정보를 이용하여, 각 기업이 속해 있는 산업군 정보를 분석해야 하며, 이를 통해 동일한 산업군에 속해 있는 다른 기업에 대한 현황 파악 및 비교 등 비즈니스 정보를 분석할 수 있다.

• Journal of Korean Electronics
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• v.28 no.3
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• pp.30-31
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• 2008

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.58-67
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• 2024

In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.285-309
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• 2001

The industry information grows faster than any other information resources in the Internet age. Unfortunately, however, there is no consensus on the standard of the classification among the information providers of the industry fields. This may a problematic issue not only in building a continuous and systematic development of the industry information, but also in the use of the information among the users. This study aims to propose a well-structured and/or an efficient classification scheme for the industry information to help the users with easy to retrieve the Internet resources. To do this, we analyzed the subject classification scheme of the domestic industry information on the web sites, which is largely adopted the \"Korean Standard for the Industry Classification\". In addition, we suggested the principle of the subject classification and their hierarchial structure derived from the analysis of the knowledge and document classification scheme. As a result, it was suggested an optimized industry classification scheme based on the analysis of the validity test of classification item measured by the quantitative analysis of the industry information, which it currently accessible through the Internet. Internet.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.151-171
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• 2012

In applying RFID/USN technology to various industries, it is needed to solve the problem caused by the system differences. Accordingly, this study introduces the common standard platform concept, and suggests the standard data scheme which provides the uniform perspective of classifying supply chain data and of using vocabularies. We selected several industry areas applicable for the platform, which are pharmaceutical, cosmetics, food and liquor industry. We collect and organize terminologies used in the supply chain of each industry, and then classify them according to the defined data attributes. The standardized vocabularies are suggested based on the contextured scheme of data classification. This study could provide more convenient way of communication between business partners, system developers and users of the platform.

• Review of KIISC
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• v.28 no.6
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• pp.25-32
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• 2018

국방과학기술 중 국가안보를 위해 보호해야 하는 기술을 방위산업기술로 정의하고 있다. 방위산업기술보호법의 대상기관은 보유 또는 연구개발 중인 방위산업기술을 식별한 후, 방위산업기술 정보를 적절한 보호등급으로 분류하여 보호하여야 한다. 이를 위해서는 국방과학기술 정보의 분류체계 국가 표준이 수립되어야 하지만 아직까지 분류체계가 정립되어 있지 않고 대상기관 별로 자체 내규로 정하도록 지침이 마련 중으로 향후 혼란을 야기할 수 있어 이에 대한 개선이 필요하다. 본 논문에서는 현행 국방과학기술 정보의 분류체계와 미국 국방부의 과학기술 정보의 분류체계를 비교하고 발전방향을 고찰해본다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.75-77
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• 2014

항만물류산업은 교역과 부가가치 창출, 높은 경제적 효과를 지닌 중요한 산업으로 그 영역이 점차 확대되고 있다. 항만물류산업의 효율화는 국가 경쟁력을 증대할 수 있는 방안 중 하나이며, 다수의 선행연구에서 그 영향에 대해 연구가 진행되었다. 본 연구의 산업 분류의 기준이 되는 한국표준산업분류의 9차 개정을 활용하고, 2010년 최초 시행된 경제총조사 자료를 활용하여 울산지역을 대상으로 항만물류산업이 지역경제에 미치는 영향을 분석하고, 우리나라 5대 항만도시간 항만물류산업을 비교하였다.

• The Journal of Korean Association of Computer Education
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• v.7 no.4
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• pp.51-60
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• 2004

This paper proposes an automated coding system of Korean standard industry/occupation for census which reduces a lot of cost and labor for manual coding. The proposed system converts natural language responses on survey questionnaires into corresponding numeric codes using information retrieval techniques and document classification algorithm. The system was experimented with 46,762 industry records and occupation 36,286 records using 10-fold cross -validation evaluation method. As experimental results, the system show 87.08% and 66.08% production rates when classifying industry records into level 2 and level 5 codes respectively. The system shows slightly lower performances on occupation code classification. We expect that the system is enough to be used as a semi-automate coding system which can minimize manual coding task or as a verification tool for manual coding results though it has much room to be improved as an automated coding system.

• Nuclear industry
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• v.23 no.1 s.239
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• pp.18-19
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• 2003

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.701-712
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• 2013

The e-learning industry status survey statistic provides information about the actual conditions of supply and demand of the e-learning industries. NIPA (National IT Industry Promotion Agency) has published the annual report of the survey results since 2004. Due to the 9th version of the KSIC (Korean standard industrial classification) revised in 2008, a refinement of the sampling design for the survey becomes necessary, especially that for the business demand sector. This article, based on the 9th revision of the KSIC, constructs a stratification of the target population used for the e-learning industry status survey on the business demand sector. Classification of strata in the business population is based on the industrial type and employment scale of business. Under the stratified population, we design a sampling scheme by using the power allocation method that enables us to satisfy a target coefficient of variation of each industrial stratum. In order to secure an accurate survey results based on the proposed sampling design, we consider the problem of calculating the design weights, derivation of parameter estimators, and formulas of their standard errors.