• Journal of Information Science Theory and Practice
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• 제10권spc호
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• pp.39-45
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• 2022

For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.

• 한국문헌정보학회지
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• 제43권3호
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• pp.197-219
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• 2009

본 연구에서는 문화예술교육 분야 분류체계의 필요성을 인식하고 패싯 기반의 분류 시스템을 설계하게 되었다. 본 연구는 체계적인 방법론을 적용하여 분류시스템을 구축하였고, 국내외 도메인 전문가와 분류전문가가 협력을 통해 분류시스템을 향상시켜 그 결과 13개의 메인 패싯과 다양한 하위 용어를 추출하였다. 본 연구에서 설계된 분류시스템의 목적은 문화예술교육의 다양한 자원을 보다 체계적이고 효율적으로 관리 이용할 수 있는 기반을 마련하는데 있으며 이는 나아가 문화예술교육 분야의 개념에 대한 문화적 격차를 해소시키는데 사용되기를 바란다.

• 한국도서관정보학회지
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• 제19권
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• pp.35-57
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• 1992

This study is an attempt to provide some helpful data for the design and the implementation of the expert system for the book-classification based on the analysis of various cases of the classification-expert system models. Following the introduction, the concepts and some features of an expert system were overviewed in the second chapter, on the basis of which the following concrete cases were introduced and analyzed in the third chapter : (1) ACN System for NC, (2) Expert System for NDC, (3) Expert System for UDC, (4) Herba Medica System, (5) Expert System for IPC, (6) Stratcyclode Project, (7) Expert System for Classification of INIS Database, (8) AutoBC System, and etc. In the conclusion, for the development of the classification-expert system, it was turned out that constructing a new system by using an AI language such as Prolog or LISP is more desirable than employing any one of expert system shells. Together it is necessary for the following requirements to be met : (1) The subject concept of a document elicited should be accurate. (2) Not only a domain knowledge but also the knowledge covering all the subjects should be represented in the knowledge-bases. (3) The knowledge-bases should be organized in such a way that the characteristics of the knowledge about classification should be well defined. (4) rule-base consisting of accurate rules about classification should be made. (5) It should be possible for classification code wanted to be generated immediately.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2007년도 정기학술발표대회 논문집
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• pp.403-407
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• 2007

정부에서는 2001년 5월에 실무적용을 위한 ${\lceil}$건설정보분류체계 구축을 위한 연구${\rfloor}$ 를 추진하여 대${\cdot}$중분류 등을 제시하였고, 그 결과 '통합건설정보분류체계 적용기준'을 건설교통부 공고로 2001년 8월에 발표하였다. 그러나 구축된 '통합건설정보분류체계'는 건설공사에서 실무활용이 미흡한실정이다. 일반적인 시설물과는 다르게 교육시설물의 경우 적용기준이 혼재되어있는 문제가 이다. 더욱이 2005년부터 교육시설물에 BTL 민간투자 사업이 시행되면서 유지관리시업무기준이나 비용계상에 대한 기준을 '통합건설정보분류체계 적용기준'에 적용할 경우 경계를 명확하게 하기 어려운 실정이다. 따라서 본 연구는 기존의 유지관리 비용분석으로 사용되었던 공종(Work)중심의 시설물 유지관리를 분석하고 이를 보완하기위해 공간(Space), 부위(Element)중심 유지관리 분석을 하여, 효율적인 유지관리 체계정립을 위한 분류의 기준을 제안하였다.

• International Journal of Knowledge Content Development & Technology
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• 제2권1호
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• pp.51-65
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• 2012

While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists' research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to achieve interoperability of the information and thus not easy to implement meaningful science technology information services through information convergence. This study aims to address the aforementioned issue by analyzing mapping systems between classification systems in order to design a structure to connect a variety of classification systems used in the academic information database of the Korea Institute of Science and Technology Information, which provides science and technology information portal service. This study also aims to design a mapping system for the classification systems to be applied to actual science and technology information services and information management systems.

• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.86-95
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• 2016

The main objective of HACCP(Hazard analysis and critical control points) system is to provide a systematic preventive approach how to control the risks in food production process. Practically, the diet classification process performed at the one of the beginning steps of the HACCP system, makes an important role of determining food safety risks and how to control them in every control point according to the different risk level of the diet. In this paper, we propose an automatic diet classification method for HACCP system using XML(eXtensible Markup Language). In order to guarantee the diet classification accuracy, we design the XML schema and attributes represents the relationship of every diet and ingredients analysing the HACCP diet classification rules. Based on the XML schema and document generation method, we develope the proposed system as client and server model that implemented XML based HACCP diet information generation module and integrated HACCP information management modules, respectively. Moreover, we show the efficiency of the proposed system with experiment results describing the school food diet information as XML documents and parsing the diet information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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• pp.859-876
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• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• 지능정보연구
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• 제1권1호
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• pp.61-72
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• 1995

Dynamic and explicit ordering of strategies is a key process in modeling knowledge-level problem-solving behavior. This paper addressed the important problem of howl to make the scheduler more knowledge-intensive in a way that facilitates the acquisition, integration, and maintenance of the scheduler control knowledge. The solution a, pp.oach described in this paper involved formulating the scheduler task as a heuristic classification problem, and then implementing it as a classification expert system. By doing this, the wide spectrum of known methods of acquiring, refining, and maintaining the knowledge of a classification expert system are a, pp.icable to the scheduler control knowledge. One important innovation of this research is that of recursive heuristic classification : this paper demonstrates that it is possible to formulate and solve a key subcomponent of heuristic classification as heuristic classification problem. Another key innovation is the creation of a method of dynamic heuristic classification : the classification alternatives that are selected among are dynamically generated in real-time and then evidence is gathered for and aginst these alternatives. In contrast, the normal model of heuristic classification is that of structured selection between a set of preenumerated fixed alternatives.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.41-48
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• 2019

In recent years, sentiment analysis research has become popular. The research results of sentiment analysis have achieved remarkable results in practical applications, such as in Amazon's book recommendation system and the North American movie box office evaluation system. Analyzing big data based on user preferences and evaluations and recommending hot-selling books and hot-rated movies to users in a targeted manner greatly improve book sales and attendance rate in movies [1, 2]. However, traditional machine learning-based sentiment analysis methods such as the Classification and Regression Tree (CART), Support Vector Machine (SVM), and k-nearest neighbor classification (kNN) had performed poorly in accuracy. In this paper, an improved kNN classification method is proposed. Through the improved method and normalizing of data, the purpose of improving accuracy is achieved. Subsequently, the three classification algorithms and the improved algorithm were compared based on experimental data. Experiments show that the improved method performs best in the kNN classification method, with an accuracy rate of 11.5% and a precision rate of 20.3%.

• 한국문헌정보학회지
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• 제25권
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• pp.185-213
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• 1993

This study is on the history of classification in Western library from ancient to Harris(1870), before Dewey. It looks into the classification systems of librarians, bibliographers, booksellers and libraries of that time. One of the earliest was the classification of the clay tablets in the Assyrian library of Assurbanipal. But the earliest recorded system in the papyrus is that which Callimachus(B.C. 310-240) devised for the library at Alexandria. In the medival, the monastry libraries used many classifications. but their libraries were very small. Gesner, Naude, Brunet, Jefferson, Edwards, Harris etc. tried to make a good classification for bibliographies and libraries. Especially Brunet made the scheme based on the French system, and it used on bibliographical classification and shelf classification in the many libraries. In 1859, Edwards made the classification scheme for the public library in the Great Britain. In 1870, Harris made the famous inverted Baconian classification and it strongly influenced the Dewey Decimal Classification.