• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.75-78
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• 2001

본 논문은 통계청에서 실시하는 인구주택 총조사로부터 획득된 각 개인의 직업 및 직종을 기술하고 있는 자연어를 입력받아 입력된 자연어가 의미하는 한국 표준 산업/구업 분류 코드의 후보들을 생성하는 산업/직업 코드 분류 도구를 제안한다. 코드 분류는 분류할 코드를 문서 범주로 간주하면 문서 분류와 동일한 문제로 생각할 수 있다. 하지만 본 산업/직업 코드 분류 문제는 입력되는 자연어의 길이가 한 두 문장 정도로 매우 짧아 문서 분류에 사용될 자질들이 개수가 주어 기존의 문서 분류 기법을 적용하기 어렵다. 이에 본 논문은 표준 코드를 기술하고 있는 내용을 미리 색인하고 입력된 자연어로부터 질의어를 생성하여 벡터공간모델로 질의어를 검색후 질의어와 일치율이 가장 높은 코드들을 분류될 후보 코드로 계시하는 정보검색 기법을 이용한 산업/직업 코드 분류 도구를 개발하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.594-601
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• 2006

Coding of occupational and industrial codes is a major operation in census survey of Korean statistics bureau. The coding process has been done manually. Such manual work is very labor and cost intensive and it usually causes inconsistent results. This paper proposes an automatic coding system based on example-based learning. The system converts natural language input into corresponding numeric codes using code generation system trained by example-based teaming after applying manually built rules. As experimental results performed with training data consisted of 400,000 records and 260 manual rules, the proposed system showed about 76.69% and 99.68% accuracy for occupational code classification and industrial code classification, respectively.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.388-390
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• 2006

본 논문은 수동 코드 분류 규칙과 예제기반의 자동 학습을 이용하는 한국어 표준 산업/직업 코드 자동분류 시스템을 제안한다. 제안된 시스템은 산업과 직업에 대하여 설명하는 자연어를 입력받아 해당 산업/직업 분류 코드를 생성하는 시스템으로 수작업으로 구축된 규칙을 적용한 후 규칙이 적용되지 않는 레코드는 예제 기반의 학습을 이용한 자동 분류 시스템에 의해서 해당 코드를 할당한다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.394-398
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• 2020

산업/직업분류 자동코딩시스템은 고용조사 등을 함에 있어 사업체 정보, 업무, 직급, 부서명 등 사용자의 다양한 입력을 표준 산업/직업분류에 맞춰 코드 정보를 제공해주는 시스템이다. 입력 데이터로부터 비지도학습 기반의 색인어 추출 모델을 학습하고, 부분단어 임베딩이 적용된 색인어 임베딩 모델을 통해 입력 벡터를 추출 후, 출력 분류 코드를 인코딩하여 지도학습 모델에서 학습하는 방법을 적용하였다. 기존 시스템의 분류 결과 데이터를 통해 대, 중, 소, 세분류에서 높은 정확도의 모델을 구축할 수 있으며, 기계학습 기술의 적용이 가능한 시스템임을 알 수 있다.

• 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.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.169-179
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• 2005

Standard industry and occupation code are usually assigned manually in Korean census. The manual coding is very labor intensive and expensive task. Furthermore, inconsistent coding is resulted from the ability of human experts and their working environments. This paper proposes an automatic code classification system which converts natural language responses on survey questionnaires into corresponding numeric codes by using manually constructed rule base and example-based machine learning. The system was trained with 400,000 records of which standard codes was assigned. It was evaluated with 10-fold cross validation and was tested with three code sets: population occupation set, industry set, and industry survey set. The proposed system showed 76.63%, 82.24 and 99.68% accuracy for each code set.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.341-347
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• 2020

This study was conducted to identify the oral function problems of workers according to Korean Standard Classification of Occupations (KSCO) and to provide evidentiary material to promote them to revise the Occupational Safety and Health Act so that workers can benefit from the collective oral healthcare project. For the research materials, it was used the 7th raw data (1st and 2nd) of National Health and Nutrition Examination Survey. It was examined the problems of chewing and speaking for the workers over 19 years old by KSCO. The connection between the types of workers and the problems of chewing and speaking has been confirmed (p<0.05). In order to improve the workers' oral healthcare, the collective oral healthcare project should be implemented. Therefore, the Occupational Safety and Health Act should be revised to hire professional health care manager with expertise, who will be host of the collective oral healthcare project.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.375-385
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• 1999

본 연구에서는 노동력수요동향조사를 위한 새로운 표본설계를 제시하였다. 새로운 표본설계에서는 전국 통계를 산출하기 위한 전국표본과 지역 특성에 맞는 고용정책 및 직업 훈련 계획 수립 등을 위한 지역통계의 수요에 따라 16개 시·도별, 규모별, 산업대분류별로 오차를 관리할 수 있는 지역표본으로 이원화하여 설계하였으며, 규모별, 산업대분류별로 오차를 관리하는 현행 표본조사의 상대표준오차를 검토하여 규모별, 산업중분류별로 합리적인 오차 관리가 가능하도록 설계하였다.

• Journal of vocational education research
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• v.35 no.4
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• pp.155-176
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• 2016

This study analyzed content of and recognition on occupations shown from Technology Home Economics textbooks of the high school elective subject having a higher connection with the career development capability for the occupational world as shown from a curriculum analysis. Hence, this study selected 3 kinds of high school Technology Home Economics textbooks with a higher share from 6 in the 2007 revised curriculum and analyzed a frequency by characteristic of occupational content and recognition on description of a occupation. Content analyzed by researchers was examined by 2 school teachers to ensure the validity and objectivity of research findings. Research findings show that there is a great deal of frequency difference in occupations suggested by publisher and unit in the Technology Home Economics subject. Also suggestion frequency of the occupational classification by level from Korean standard industrial classification did not correspond to an actual situation of employment. Occupation names suggested from textbooks occupied 3.3% of those by Korean Occupation Dictionary, showing a higher suggestion ratio at occupations preferred by adolescents. In the textbooks, occupations were suggested from reading materials, photos and illustrations more than from texts. Recognition on descriptions of occupations showed for the most part the neutral(82.8%) and the positive16.2%)', and there was no biased intention even from some negative cases(1.0%). Based on research findings, this research has significance in that it suggested things to be considered for teaching career development capability in the high school Technology Home Economics subject and need for cultivating teachers' specialty to understand occupations and instruct career development. It also suggested improvements to be required for a new curriculum textbook.

• Journal of Fisheries and Marine Sciences Education
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• v.18 no.3
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• pp.341-363
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• 2006

All industries must be cope with fast technological progress along with the economic changes experience. However, a fishery and ocean industry are something yet to study base data for HRD and classifying occupation. Therefore, this study points to major problems which related useful data of information on the fishery and ocean industry. The purpose of this study is to classify fishery and ocean occupations by KSCO. The study is carried out though review of the literature, field investigation, direct interview and an experts' meeting of 5 field majors. A proposed classification of fishery and ocean occupations is modified on several times by the meeting of experts' group. Finally, a systematic classification of fishery and ocean occupations is as follows. First of all, first rank change from fishing to fishery industry. And the second rank, fishery and ocean occupations were classified into four categories bases on the systematic and comprehensive, as it were production fisheries, fishery products and processing, fishery supplies and infrastructure, fishery services. Each rank of classifying occupation is from two to four steps based on the occupation cluster.