• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.529-532
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• 2006

과학기술 연구자들의 협업을 지원하기 위해서 정보 자원 공유에 기반한 정보 유통 체제가 필요하나 현재 정보 유통 체제에서는 서로 이질적인 형태로 정보가 표현되어 있기 때문에 정보 공유의 기술적 한계를 갖고 있다. 그리고 대량의 정보 속에서 사용자가 원하는 정보를 선별하여 제공하기 위해서는 새로운 정보 유통 플랫폼이 필요하다. 본 논문에서는 지식 기반 정보 유통 플랫폼 상에서 이용되는 국가과학기술 R&D 기반정보를 지식화하기 위해 국가과학기술 R&D 기반정보 온톨로지를 구축하여 이용함으로써 각 기관별로 관리하고 있는 인력, 성과물 등의 과학기술 R&D 기반 정보의 표준화된 지식관리 체계로 이용할 수 있다. 우리는 국가과학기술 R&D 기반정보 온톨로지를 구축하기 위하여 한국과학기술정보연구원(KSITI) 내부 성과물 정보의 실제 데이터들을 이용하여 온톨로지의 Individuals를 생성하였다. 정보 유통 플랫폼에서 온톨로지 형태로 구축된 지식을 이용하면 과학기술 R&D 기반정보에 대한 효율적인 관리가 가능하고, 정형화된 형태의 지식으로 개념화했기 때문에 지식 데이터의 공유와 재사용이 가능하다. 또한 단순 질의 검색이 아닌 의미 기반 추론을 이용한 지식 검색이 가능해지는 장점을 가진다. 우리가 구축한 국가 과학기술 R&D 기반정보 온톨로지를 이용하여 정보유통플랫폼(OntoFrame-K)에서 연구자 네트워크, 연구자 추적, 연구맵의 추론 서비스를 제공한다.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.231-234
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• 2006

Semantic web ontologies can be viewed as logic-based domain-oriented contents which allow distributed and heterogeneous information to be semantically integrated, automatically circulated, and enable implicit knowledge to be reasoned. This paper describes the 'Science and Technology Research Area' ontology which is being developed by the Korea Institute of Science and Technology Information (KISTI). This ontology was defined to assist actual researchers and project planners to grasp the researchers community from a variety of viewpoints. We describe classes and properties as ontology components and exemplify the representation of real instances in the ontology. In order to represent the identities of real world instances within the ontology, the above ontology employs both class-dependent URI assignment schemes and the identity resolution methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.87-88
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• 2008

As an information service system based on semantic web technology, $OntoFrame^{(R)}$ takes aim at a framework for providing analysis and fusion services of academic information. It currently consists of three parts: ontologies representing knowledge schema derived from academic information, $OntoURI^{(R)}$ which makes academic information into knowledge, and $OntoReasoner^{(R)}$ which performs inference and search on the knowledge. Unlike existing search engines which provides simple search services, our system provides, based on semantic web technology, several semantic and analytic services such as year-based topic trends in academic information, related topics, topic-based researchers and institutes, researcher network, statistics and regional distribution of academic information.

• Journal of Information Management
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• v.37 no.2
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• pp.109-136
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• 2006

The development of Semantic Web basically requires knowledge which is induced by the formalization and semantization of information, and thus ontology should be introduced as a knowledgization tool. URI(Uniform Resource Identifier) is an indispensible scheme to uniquely indicate individuals on ontology. However, it is difficult to find the use cases of identifiers or URIs in real data sets including science & technology publications. This paper describes the method to construct, manage, and serve reference information based on URI which is a crucial component on establishing national R&D reference information ontology. We expect the reference information which was acquired from about 7,000 proceeding papers would be adopted to Semantic Web applications such as researcher network analysis and outcome statistics.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.67-76
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• 2019

In this paper, we propose an efficient object classification method based on semantic segmentation for multi-labeled image data. In addition to various pixel unit information and processing techniques such as color information, contour, contrast, and saturation included in image data, a detailed region in which each object is located is extracted as a meaningful unit and the experiment is conducted to reflect the result in the inference. We use a neural network that has been proven to perform well in image classification to understand which object is located where image data containing various class objects are located. Based on these researches, we aim to provide artificial intelligence services that can classify real-time detailed areas of complex images containing various objects in the future.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Review of KIISC
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• v.19 no.3
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• pp.22-28
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• 2009

유비쿼터스 컴퓨팅의 확산과 사용자의 이동성 증가는 사용자에게 적합한 서비스를 제공해주기 위해서 미리 설정된 특정 서비스나 정책으로는 구현하기 어렵게 되었음을 의미한다. 또한 사용자의 서비스 영역은 미리 정의된 환경으로 제한되지 않고 사용자가 이동하는 모든 영역으로 확대되고 있다. 따라서 기존의 홈네트워크와 같은 특정 기술 및 서비스 시스템을 유비쿼터스 컴퓨팅에 적용하는 것에는 한계가 존재한다. 서비스 영역의 확장과 융합, 사용자의 생활권을 포함하는 산업적인 부분에까지 유비쿼터스 컴퓨팅은 확산됨에 따라서 다각적인 IT산업 분야에서 새로운 연구가 필요하게 되었다. 이러한 새로운 산업IT요구에 따라 다양한 서비스 영역으로 적응적인 시스템의 구현과 정보보호 및 서비스 구현에 대한 동적이며 적응적인 정책의 구현이 시급한 실정이다. 따라서 본 논문에서는 서비스의 확장과 융합에 따라 발생될 수 있는 정책적인 문제점을 분석하고 유비쿼터스 컴퓨팅을 위한 정책을 제안하고자 한다. IT 기술을 다양한 산업 분야로 확장하기 위해서는 지능적인 서비스에 대한 구현 방안이 고려돼야 할 것이다. 그리고 지능적 서비스를 위한 정책의 운영, 상황에 따른 추론 기술 및 서비스 관리 기술에 대한 연구가 병행되어야 한다. 단순히 기존 홈네트워크에서 적용되던 특정 상황에 따른 서비스의 구현이나 한정된 상황 정보(Context)에 대한 관리 기술만으로는 고도화된 산업IT기술을 실현하기 어렵다. 따라서 확장성 및 효율성을 증대하기 위한 방안으로 이기종 환경 네트워크 시스템에서 발생 가능한 보안 문제 해결을 위한 multi-resolution 기술과 온톨로지 기반의 상황 정보 관리 기술을 제안한다.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.51-58
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• 2018

As the amount of users and data of NS explosively increased, research based on SNS Big data became active. In social mining, Latent Dirichlet Allocation(LDA), which is a typical topic model technique, is used to identify the similarity of each text from non-classified large-volume SNS text big data and to extract trends therefrom. However, LDA has the limitation that it is difficult to deduce a high-level topic due to the semantic sparsity of non-frequent word occurrence in the short sentence data. The BTM study improved the limitations of this LDA through a combination of two words. However, BTM also has a limitation that it is impossible to calculate the weight considering the relation with each subject because it is influenced more by the high frequency word among the combined words. In this paper, we propose a technique to improve the accuracy of existing BTM by reflecting semantic relation between words.

• Korean Journal of Biological Psychiatry
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• v.29 no.1
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• pp.15-21
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• 2022

Objectives Maltreatment experiences can alter brain function related to emotion regulation, such as cognitive reappraisal. While dysregulation of emotion is an important risk factor to mental health problems in maltreated people, studies reported alterations in brain networks related to cognitive reappraisal are still lacking. Methods Twenty-seven healthy subjects were recruited in this study. The maltreatment experiences and positive reappraisal abilities were measured using the Childhood Trauma Questionnaire-Short Form and the Cognitive Emotion Regulation Questionnaire, respectively. Twelve subjects reported one or more moderate maltreatment experiences. Subjects were re-exposed to pictures after the cognitive reappraisal task using the International Affective Picture System during fMRI scan. Results The maltreatment group reported more negative feelings on negative pictures which tried cognitive reappraisal than the no-maltreatment group (p < 0.05). Activities in the right superior marginal gyrus and right middle temporal gyrus were higher in the maltreatment group (uncorrected p < 0.001, cluster size > 20). Conclusions We found that paradoxical activities in semantic networks were shown in the victims of maltreatment. Further study might be needed to clarify these aberrant functions in semantic networks related to maltreatment experiences.

• Journal of the Korean Society for information Management
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• v.15 no.3
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• pp.133-150
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• 1998

For the purpose of new‘organizational knowledge centric knowledge management’, this paper proposes the knowledge creating organizational memory which shows the knowledge creation in organization according to the dialectical circulation between the domain knowledge and the task knowledge, based on the Yin Yang theory. This paper defines two kinds of organizational knowledge such as the domain knowledge and task knowledge and designs them in the pursuit of its lifecycle. Knowledge creating organizational memory is designed to three knowledge components that circulate through the domain knowledge and the task knowledge according to the object-oriented methodology. Organizational knowledge is designed into the graphical structure of ( i ) knowledge ( ⅱ ) relation between knowledge objects and ( ⅲ ) degree of relation, which receive the legacy of organizational knowledge such as data schema, process model and knowledge base. This design of organizational knowledge can be applied to CBR(Case Based Reasoning), one of knowledge mining tools to create new organizational knowledge.