• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.19-43
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• 2007

The purpose of this study is to distinguish industrial clusters in Korea. Based on I/O table in 2000, coefficient matrix was calculated and factor analysis was performed on the matrix. Among 38 derived industrial clusters, 5 of them were unreported clusters, which were indistinguishable. Once these 38 industrial clusters were differentiated according to I/O table, final results of clusters were produced as I/O table was converted into KSIC (Korean Standard Industry Code). Since existing studies on industrial cluster have been focused on qualitative methods such as case studies and interviews, it is expected that this study could contribute to carry out more systematic and efficient methodology.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.331-334
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• 2001

생산성 있는 소프트웨어 개발 및 관리를 위한 기술적, 산업적 전략은 웹 환경 하에서 컴포넌트 기반의 소프트웨어 개발(CBD : Component Based Development)로 점차 귀결되고 있다. 나아가 정보 공유의 투명성이나 비즈니스 로직의 독립적 패키징과 같은, 이 두 개의 기술들이 개별적으로 가지는 특성과 장점들을 결합한 웹 서비스로 전환되고 있다. 따라서 컴포넌트 중심의 웹 서비스를 위한 인프라 환경의 지원이 무엇보다 중요하게 되었다. J2EE는 이러한 요구를 수용하기 위한 가장 표준화된 플렛폼 중의 하나로, 다중 계층의 엔터프라이즈 솔루션을 위한 간단한 개발과 전개, 관리 방식을 보장한다. 본 논문에서는 CBD의 완성을 위한 실제적인 접근으로서 J2EE 환경의 EJB 컴포넌트를 위한 코드 자동 생성 도구를 개발한다. 이를 위해 EJB 컴포넌트를 구성하는 코드의 속성들을 분석하여 보편적인 EJB 컴포넌트의 템플리트를 설계하였다. 또한 도구 구축의 과정에서 세부적인 EJB 생성기의 구조와 기능적 특성을 명시화하고 개발에 필요한 EJB 컴포넌트 정보를 정의, 분류하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.1
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• pp.13-20
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• 2006

In this paper, we constructed a spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the legitimate mil. The definite information is the mail sender's information, URL, a certain spam keyword list, and the less definite information is the word lists and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning. According to our results the spam precision was increased if more lexical information was used as features, and the spam recall was increased when the concept codes were included in features as well.

• Convergence Security Journal
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• v.19 no.1
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• pp.11-17
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• 2019

Recently, the abuse of Internet technology has caused economic and mental harm to society as a whole. Especially, malicious code that is newly created or modified is used as a basic means of various application hacking and cyber security threats by bypassing the existing information protection system. However, research on small-capacity executable files that occupy a large portion of actual malicious code is rather limited. In this paper, we propose a model that can analyze the characteristics of known small capacity executable files by using data mining techniques and to use them for detecting unknown malicious codes. Data mining analysis techniques were performed in various ways such as Naive Bayesian, SVM, decision tree, random forest, artificial neural network, and the accuracy was compared according to the detection level of virustotal. As a result, more than 80% classification accuracy was verified for 34,646 analysis files.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.11a
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• pp.33-45
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• 2001

Korean standard industrial/occupational classification has been the basis of producing accurate statistical data related with our industrial structure and distribution of industry and occupation since 1960. But coding over several million records not only requires high cost in the aspects of time and manpower but also has many problems in accuracy and consistency. Therefore, we got to develop the automatic coding system in order to work out these problems of manual coding. This paper shows the structure of our system and the result of experiment over survey data of 2,000 Census.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.678-683
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• 2018

This study deals with the analysis of a technology convergence of the IoT(Internet of Things) which is the key technology of the fourth industrial revolution. For this purpose, 77 patents with the Main Category CPC code G06Q50/10(Electronic Commerce Service) among the IoT patents filed after 2014 were analyzed. As a result of the Main-Sub Category analysis of CPC codes, the IoT has a strong relationship between "Electronic Commerce Service (G06Q50/10)" and G06Q(49 cases), H04L(40 cases), G08B(24 cases), G05B(21 cases), H04W(21 cases), H04N(16 cases), and so on. By using the methodology in this study, we can contribute the establishment of technology strategy and new value creation from the prediction of the possibility of the combination of technologies and to develop new patents among various new technologies.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.219-225
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• 2015

Nowadays, technologies are changing through industrial fusion and government & corporates need to predict the flow & direction of technologies. These flow & direction can be grasped through the analysis of patent information. The patent information uses the common classification codes in the world, and it is possible for the quantitative analysis based on objective data with the time information of technical area. The methods of patent analysis analyzed the technology fusion by using citation analysis & simultaneous classification analysis. This research analyzed patent information which used as an index to measure the technical innovation in the society based on knowledge, and would like to analyze technical trends and to describe the way of improvement in the future based on the aviation industry which is the representative fusion/complex industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.680-684
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• 2020

최근 국내에서는 식품에 대한 관심도가 높아짐에 따라 먹거리에 건강·환경·미래지향적 가치가 부여되고 있으며 식품 산업에서도 신규 식품 개발이 증가하는 추세이다. 식단을 구성할 때 기준이 되는 식품교환표는 개정과정에서 많은 인력과 시간이 소요되기 때문에 식품 섭취 변화를 신속하게 반영하기 어렵다. 본 논문에서는 식품교환표의 활용도를 높이기 위한 식품교환표 갱신 기법을 제안한다. 제안 기법은 의사결정트리 모델을 학습하여 새롭게 추가된 식품의 정보를 바탕으로 식품군을 분류하여 식품교환표를 갱신한다. 이는 영양 관리가 필요한 당뇨병 환자 등에게 실용적이며 기호성·다양성이 높은 식단을 구성하는 데 도움을 준다.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.377-385
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• 2014

This study is aimed to introduce the newly developed mobile application for effective provision of assistive devices for people with disabilities in South Korea. By combining of ICF code and ISO 9999 code, more effective way of searching user fit assistive device information and selecting appropriate assistive devices were possible. 10 people with visual impairment were recruited for an usability testing. For the data analysis, paired t-test were used and confidence interval was 95%. The result showed newly developed mobile application was more effective in comparison with on-line based assistive device information. The outcome of this study will enhance the provision of assistive devices for people with disabilities more effectively within better user understanding of their needs and compensate for their body function as well as environmental barriers.