• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.142-144
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• 2005

전자메일이 일상의 연락수단일 뿐만 아니라 여러 가지 목적의 업무처리에 있어서도 중요한 통신수단으로 이용되고 있다. 이에 따라 전자메일의 중요도를 자동적으로 판정하는 문서 필터링 방법이 연구되고 있다. 본 논문은 수신된 메일문서에서 송신처, 제목, 문서유형, 시간제한 둥의 다중속성을 조합하여 구조적인 지식을 생성하여 전자메일을 자동으로 필터링하는 시스템을 구현한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Journal of Environmental Policy
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• v.6 no.2
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• pp.97-122
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• 2007

In 2006, the Ministry of Environment of the Republic of Korea, completed the construction on national environmental geographic informations including National Environmental Assessment Map, Ecological Map, Land Cover Map and so on. At this point of time, it is necessary to establish the advance strategy on national environmental geographic information, considering the complicated characteristics. Therefore, this study suggests the advance strategy on national environmental geographic information, reflecting results of analyzing the given condition and the trend of informatization. National environmental geographic information has spacial quality to be managed dispersedly in a department unit or an operations unit. According to this quality, requirements for users who need the policy based on national environmental geographic information and complex information are not satisfactory. And, the information system centering the process of administrative affairs should be converted to one putting decision supporting first in importance. Therefore, this study sets up "the realization of the sustainable land management system by advancing national environmental geographic information" as the vision of the advancing strategy. In order to accomplish the vision, this study established the purpose as follow; constructing strategic and geographic information based on knowledge, arranging the foundation to open information to the public transparently, building expanded and integrated national environmental geographic information, embodying the environmental administration based on national environmental geographic information, enhancing the efficiency of national environmental geographic information, and supporting efficiently the process of administrative affairs. And this study suggests executive plans to achieve the vision and the purpose as next; developing the quality control program to verify the information confidence, building the system to integrate and to provide environmental information, collecting information, readjusting laws and regimes in parts of the construction, the application and the management of the system, and operating the task process, human power, organization and information technology. This study puts the emphasis on providing the turning opportunity politically which is possible to make sure of the information confidence in quality, advancing from the expansion of one in quantity. However, this improvement strategy doesn't reflect all national environmental geographic information and current status of environmental administrations. Therefore, for applying the result of this study to the actual environmental administration, it is necessary to discuss regularly the systematic categorization of national environmental geographic information, to interview with the contracting parties and so on hereafter.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.3
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• pp.93-106
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• 1999

In this paper, the basic architecture of an agent system was designed and a KQML(Knowledge Query and Manipulation Language) handler was implemented to handle 'tell', 'ask', 'handles' and 'interested' KQML performatives. The basic architecture of an agent system consists of a KQML handler, a KIF interpreter and a Flow control code. Agents use KIF(Knowledge Interchange Format) to represent the actual knowledges that are transmitted. They communicate others via an external language called KQML, which contains contents of messages written in KIF. The KQML handler controls communication. Contents of messages through it are stored and interpreted by the KIF interpreter. The flow control code controls the flow of program and information and performs engineering tasks. It gets knowledges from the knowledge base of the KIF interpreter and the other agents.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2007.10a
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• pp.131-139
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• 2007

국토기본법과 국토의 계획 및 이용에 관한 법률은 국토의 지속 가능한 발전을 위한 정책 및 계획을 규정하고 있다. 이를 효율적으로 달성하기 위한 수단으로GIS를 기반으로 공간의사결정 지원체계 구축에 대한 수요가 높아지고 있다. 이는 그 동안 행정업무를 위한 자료관리 중심의 정보화에서 공간자료분석을 기반으로 한 정보화에 대한 새로운 수요라고 할 수도 있다. 그러나 국토공간계획을 지원하기 위한 의사결정지원체계를 성공적으로 구축하기 위해 해결해야 할 많은 과제들이 있다. 본 연구는 국토공간계획을 위한 의사결정지원체계를 구축하는데 장애가 되는 과제를 파악하고, 해결방향을 제시하는데 목적을 두고 있다. 이를 위해 전문가를 대상으로 한 델파이 조사를 실시했다. 본 연구는 공간의사결정지원체계의 설계 및 개발에 영향을 미치는 주요 요인을 중심으로 research questions를 가지고 접근했다. 시스템 설계 관점에서 처리결과에 영향을 미치는 요인으로 입력되는 자료와 지식, 분석처리하는 방법, 인터페이스 등을 중심으로 research question을 설정했다. 시스템 개발과 관련하여 개발도구 확보, 이해관계자 참여 방안, 시스템의 지속성 확보 등을 중심으로 research questions를 설정했다. 마지막은 향후 공간의사결정 지원체계의 연구 및 개발을 효율적으로 수행하기 위한 파트너쉽에 대한 research question이다. 지금까지 국내에서 공간의사결정지원체계 구축과 관련해 기초적인 이론이나 방법론에 대한 연구가 미흡했다. 대부분 외국의 연구 및 개발사례를 소개하는 수준에 불과하다. 특히 공간의사결정지원체계를 구축하거나 운용하는 기반기술인 개발도구에 대한 기술수준이 상당히 미흡하다. 조사결과에서 공개소프트웨어 도입에 대한 필요성 강조가 이를 반증하고 있다. 또한 시민사회의 성숙, 다양한 사회단체 출현 등으로 국토공간계획 과정에 이해관계자 참여정도가 질적 양적으로 높아질 것으로 예상된다. 그러나 이에 대응하기 위한 기술, 기법 등에 대한 연구는 매우 미흡하고 단편적으로 관련 기술을 소개하는 정도이다. 국토공간계획 및 정책과 관련한 다양한 문제해결을 위한 공간의사결정지원체계를 구축하기 위해서 장기간에 걸긴 단계적 접근이 필요하다. 국토공간계획은 우리나라만의 자연 환경 및 인문환경의 특성이 반영되어야 할 것이다. 이를 위해 우리의 개발방법론, 우리의 기술이 개발되어야 하며, 이를 체계적으로 구현할 수 있는 협력체계 구축이 필요하다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.1
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• pp.67-75
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• 1993

The urban expansion and the modernization of the urban infrastructure need a new technology to manage the facilities. The sewer management, one of the urban infrastructures, requires geographical information systems(GIS) for this purpose, and can be supported by the expert system. Consequently, non-professionals can use this system conveniently. In this study, the search and retrieving capacity of the relational database management system(DBMS) and the chain topology generator of the vector-based GIS were integrated into the sewer management system together with the expert knowledge. This system can predict the sewer volume charge by the simulation, and automate these procedures. This system is also user-friendly by using the user-interface. Finally, the system was applied to one of the Seoul drainage districts and tested.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.479-486
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• 2013

The data model that can be said as skeleton of the information system constitutes important 2 axles in the information system together with the process model. There is entity, properties, relation as key factors of the data model, and entity is the most fundamental factor in the data model, and thus total data model becomes vague if not deriving entity definitely. This study dealt with entity deduction only. Deducing methods of existing entity depended on experiences, task knowledge of designers and clear procedures were not suggested, so there were many difficulties in approaching them from beginners or unskilled persons. For giving helps in solving the problem, this study proposes entity- deducing procedures based on tasks that can derive entity with a systematic process at previously derived target businesses through suggested methods from advancing researches. And the study enabled proposing procedures on imaginary tasks to be applied, objecting to undergraduates who had not experiences on the data modeling, and then verified suggesting process through a similarity checking between best answers with deduced entity by students after taking impossible points of comparing existing methods with suggesting process into consideration. By doing so, deducing entity closely to the best answer was confirmed accordingly. Therefore, a fact could be confirmed that beginners were able to deduce entity closely to the best answer even if letting beginners who had not experiences on the data modeling be applied to unfamiliar tasks. Regarding researches on properties and relation deduction besides entity, this study leaves them to next time.

• The Journal of Bigdata
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• v.7 no.2
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• pp.139-152
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• 2022

Engineering's work area for plants is a technical area that directly affects productivity, performance, and quality throughout the lifecycle from planning, design, construction, operation and disposal. Using the different types of data that occur to make decisions is important not only in the subsequent process but also in terms of cyclical cost reduction. However, there is a lack of systems to manage and analyze these integrated data. In this paper, we developed a knowledge base-based plant engineering analysis platform that can manage and utilize data. The platform provides a knowledge base that preprocesses previously collected engineering data, and provides analysis and visualization to use it as reference data in AI models. Users can perform data analysis through the use of prior technology and accumulated knowledge through the platform and use visualization in decision-support and systematically manage construction that relied only on experience.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.15-20
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• 2016

This paper describes the construction of knowledge data retrieval management system based on medical image CT. The developed system is aimed to improve the efficiency of the hospital by reading the medical images using the intelligent retrieval technology and diagnosing the patient 's disease name. In this study, the medical image DICOM file of PACS is read, the image is processed, and feature values are extracted and stored in the database. We have implemented a system that retrieves similarity by comparing new CT images required for medical treatment with the feature values of other CTs stored in the database. After converting 100 CT dicom provided for academic research into JPEG files, Code Book Library was constructed using SIFT, CS-LBP and K-Mean Clustering algorithms. Through the database optimization, the similarity of the new CT image to the existing data is searched and the result is confirmed, so that it can be utilized for the diagnosis and diagnosis of the patient.