• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.377-392
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• 2015

In today's data-driven society, we've been hearing a great deal about the power of Big Data over the last couple of years. At the same time, it has become the most important issue that the problems is caused by the data collection, management and utilization. Moreover, Big Data has a wide applications ranging from situation awareness, decision-making to the area to enable for the foreseeable future with man-made and analysis of data. It is necessary to process data into meaningful information given that the huge amount of structured and unstructured data being created in the private and the public sector, even in disaster management. This data should be public and private sector at the same time for the appropriate linkage analysis for effective disaster management. In this paper, we conducted a literature review and case study efficient Big Data to derive the revitalization of national disaster management. The study obtained data on the role and responsibility of the public sector and the private sector to leverage Big Data for promotion of national disaster management plan. Both public and private sectors should promote common development challenges related to the openness and sharing of Big Data, technology and expansion of infrastructure, legal and institutional maintenance. The implications of the finding were discussed.

• Journal of the Economic Geographical Society of Korea
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• v.3 no.2
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• pp.81-96
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• 2000

The study examines the present condition and prospects of venture firm accumulation center in the case of kwan-ak venture town. The survey shows most of companies have been founded since 1997. Their major items are software development and the average employees are under 10 workers. According to the questionary about the type of R&D and the level of innovation, technology innovation such as the development of new product is advanced whereas tacit innovation like inter-firm cooperation is very weak. And the source of idea and information is concentrated on the within-firms and research center As a result of the analysis of regional linkage, the dependence of production and R & D is large on kwan-ak-gu, but sales and information services have emphasis on Seoul area. In the light of the affiliation of inter-firm, they response sympathy with cooperation, but could not strengthen their commercial ties yet. At last, the policy for venture firm accumulation center must intend to make tacit measures through inventing of system instead of the simple means such as the assistance of location, finance and tax.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.556-561
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• 2020

The aging and declining agricultural population in the modern society requires improvement of the agricultural environment and is one of the representative problems. And since most of the work systems always require a transport work, the ratio of labor consumed in the transport work is very high. Accordingly, many types of transport vehicles are being developed and sold, and in the early days, most of them are powered transport vehicles using fossil fuels. However, it is paying attention to next-generation eco-friendly energy such as hydrogen, fuel cells, solar power, and bio due to the strengthening of international environmental regulations such as global warming and the Convention on Climate Change and the depletion of fossil fuels. Therefore, in this study, the ultimate goal is to develop an eco-friendly, easy-to-operate, safe agricultural electric vehicle that replaces fossil fuels. It was designed with a focus on controlling a wide range of vehicle speeds and securing stability of electric agricultural vehicles. Considering the performance and design, it is composed of a frame, a driving part, a steering part, and a controller system, and we are going to review and manufacture each part. It is believed that the manufactured electric vehicle for agriculture can be easily and conveniently operated in an agricultural society where young manpower is scarce, and can be helpful to the agricultural society through high efficiency.

• The Korean Journal of Archival Studies
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• no.16
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• pp.97-146
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• 2007

Those days when people used paper to make up and manage all kinds of documents in the process of their jobs are gone now. Today electronic types of documents have replaced paper. Unlike paper documents, electronic ones contribute to the maximum job efficiency with their convenience in production and storage. But they too have some disadvantages; it's difficult to distinguish originals and copies like paper documents; it's not easy to examine if there is a change or damage to the documents; they are also prone to alteration and damage by the external influences in the electronic environment; and electronic documents require enormous amounts of workforce and costs for immediate measures to be taken according to the changes to the S/W and H/W environment. Despite all those weaknesses, however, electronic documents increasingly account for more percentage in the current job environment thanks to their job convenience and efficiency of production costs. Both the government and private sector have made efforts to come up with plans to maximize their advantages and minimize their risks at the same time. One of the methods is the Authorized Retention Center which is described in the study. There are a couple of prerequisites for its smooth operation; they should guarantee the legal validity of electronic documents in the administrative aspects and first secure the reliability and authenticity of electronic documents in the technological aspects. Responding to those needs, the Ministry of Commerce, Industry and Energy and the Korea Institute for Electronic Commerce, which were the two main bodies to drive the Authorized Retention Center project, revised the Electronic Commerce Act and supplemented the provisions to guarantee the legal validity of electronic documents in 2005 and conducted researches on the ways to preserve electronic documents for a long term and secure their reliability, which had been demanded by the users of the center, in 2006. In an attempt to fulfill those goals of the Authorized Retention Center, this study researched technical standard for electronic record information package of the center and applied the ISO 14721 information package model that's the standard for the long-term preservation of digital data. It also suggested a process to produce and manage information package so that there would be the SIP, AIP and DIP metadata features for the production, preservation, and utilization by users points of electronic documents and they could be implemented according to the center's policies. Based on the previous study, the study introduced the flow charts among the production and progress process, application methods and packages of technical standard for electronic record information package at the center and suggested some issues that should be consistently researched in the field of records management based on the results.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• 대한예방의학회:학술대회논문집
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• 2002.07b
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• pp.3-17
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• 2002

국민건강은 국가발전의 기본조건이다. 국민건강은 건강한 어린이의 출산에서 비롯되고, 건강한 어린이의 출산을 위하여 여성이 건강해야 한다 따라서 여성과 어린이 건강보호와 증진을 위한 모자보건사업은 국가보건사업 중 최우선 사업으로 추진되어야 한다. 우리나라의 모자보건사업은 1960대부터 보건소를 통하여 가족계획, 산전관리, 안전분만유도, 예방접종을 중심으로 하였다. 1980년대에 들어와 전국민의료보험의 실현과 국민생활수준의 향상 등으로 산전관리 수진율과 시설분만율이 급격히 증가하여 1990년대 후반에는 거의 100%에 도달하였고, 가족계획실천율도 1991년에 79.4%까지 증가하여 합계출산율이 1.6으로 감소하였고, 어린이 기본예방접종률도 90%이상이 되어 전염병 발생률이 현저히 감소하였다. 전통적인 모자보건사업 관련 지표들이 이렇게 향상되자 일선 보건요원에서부터 중앙정부의 정책결정권자에 이러기까지 모자보건사업에 대한 관심도가 떨어져 중앙부처의 모자보건업무 담당 부서도 축소되고, 모자보건 사업도 쇠퇴하였다. 그러나 어린이와 여성의 건강실태를 자세히 들여다보면 심각한 문제들이 대두되고 있다. 시설 분만율의 증가에 따라 제왕절개분만율이 40%대까지 급증하였고, 모유수유률은 10%대로 떨어졌다. 어린이의 체격은 커지고 있으나 체력은 떨어지고, 비만한 어린이가 급증하여 당뇨병과 같은 성인병 유병률이 어린이들에게 증가하고, 사고에 의한 어린이 사망과 장애가 늘고 있다. 또한 청소년들의 흡연율과 음주률이 증가하고, 성적 성숙이 빨라지고 사회의 개방풍조로 성(性)활동 연령이 낮아지고 성활동이 증가하여 혼전임신과 성폭력이 증가하고 있다. 여성들은 일찍 단산하고, 폐경 연령은 높아지고, 평균수명은 길어져 중년기와 장년기 그리고 노년기가 길어져 각종 만성질환에 이환될 기회가 늘어났다. 이러한 시기의 중요 건강문제들은 뇌혈관질환, 폐암, 유방암, 골다공증, 뇨실금 등과 같이 해결하기 어려운 것들이다. 이렇게 어린이와 여성들에게 새로운 건강문제들이 대두되고 있으나 이에 대한 대응정책이 없었고, 따라서 새로운 모자보건사업이 개발되지 않았으며 일선 보건요원의 훈련도 없었다. 그리고 이러한 건강실태를 파악하여 대책을 마련하고, 보건사업을 평가할 수 있는 보건정보체계가 없는 실정이다. 1990년대 중반에 소수의 학자들이 어린이와 여성건강문제의 심각성을 제기하고, 모자보건사업 활성화의 필요성을 주장하여 보건복지부가 '모자보건선도보건사업'이라는 이름으로 1999년부터 2001년까지 3년간 23개 보건소에서 시범사업을 시행하였다. 이 시범사업에서는 한정된 자원으로 여성과 어린이 보건문제를 효과적으로 해결하기 위해 새로운 보건사업의 개발과 효율적으로 수행하는 방법의 개발에 역점을 두어 많은 성과를 거두었다. 시범사업의 경험을 바탕으로 2002년에는 전국의 45개 보건소로 확대해나가고 있다. 모자보건선도보건사업에서는 임산부가 대상이었던 기존의 모자보건사업과는 달리 신생아, 영유아, 학동기 어린이, 청소년, 그리고 신혼부부에서부터 장년기 여성에 이르기까지 사업대상을 확대하고 생애주기에 따라 지역사회 건강문제해결을 목표로 한 보건사업을 수행하도록 하였다. 사업수행 과정에서 보건소는 지역내 대학과 협력체계를 구축하여 기술적 지원을 받고, 보건요원의 교육 훈련을 통해 사업기획 능력과 전문지식과 기술을 향상시켰고, 보건교육에 필요한 시설과 장비를 구입하였고, 민간의료기관과 연계하여 보건서비스의 질을 향상시켰다. 모자보건 선도보건소에서 제공하는 서비스는 취약계층 중심의 보건교육, 상담 및 지도, 고위험대상자 조기발견 및 민간기관 의뢰 및 주구관리, 질병 조기발견을 위한 검진 의뢰, 지역 보건통계 생산과 관리, 그리고 지역내 가용자원 안내 등이며, 저소득층에 대해서는 민간의료기관에 의뢰 또는 검진비용을 지원하였다. 이와 같이 지역사회 민간기관과 협력체계를 구축함에 따라 대상자를 지속적으로 관리할 수 있는 정보를 공유하게 되었고, 건강증진 및 질병예방, 치료, 사후관리를 포함한 지속적이고 포괄적인 서비스를 제공할 수 있게 되었다. 특히 고위험 및 건강의심 대상, 임부와 장년기 여성에 대해서는 건강검진서비스를 과감히 민간기관에 의뢰, 위탁하친 보건소는 상담자, 정보관리자로서의 역할로 전환할 수 있었다. 그러나 사업관리자의 양적 평가에 대한 고정관념과 질적 평가에 대한 인식부족, 기본 생정통계와 정보체계의 미비로 인한 부정확한 통계생산, 사업요원의 전문지식과 기술 부족, 그리고 인력부족 등이 문제점으로 대두되었다. 효율적인 사업확산과 조기 정착을 위해 중앙정부의 일관성 있는 정책과 재정적 지원이 필수적이며, 보건정보체계확립, 그리고 공공보건기관과 민간의료기관간의 공식적인 협력체계확립이 필요하다. 사업추진 모니터링 및 평가, 조정을 위하여 중앙에 '모자보건 선도사업 기술지원단'을 구성하여 운영하고, 프로그램 운영이 잘되는 보건소를 특성화 보건소로 지원 육성하고, 사업요원의 업무 적정화를 위한 보건소 조직과 기존 보건사업체계의 평가와 재편이 필요하다. 보건사업요원의 자질 향상을 위한 지속적인 교육 훈련 시스템과 보건통계생산 관리를 위한 정보체계의 구축이 요구된다. 모자보건사업관련 보건교육자료를 수집하고 개발하여 전국 보건소에 공급하는 중앙 보건교육자료 및 정보센터가 필요하다.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.