• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.169-180
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• 2009

The conventional paper retrieval is the keyword-based search and as a huge amount of data be published, this search becomes more difficult in retrieving information that user want to find. In order to search for information to the user's intent, we need to introduce semantic Web that represents semantics of Web document resources on the Internet environment as ontology and enables the computer to understand this ontology. Therefore, we describe a paper retrieval system through OWL(Ontology Web Language) ontology-based reason in this paper. We build the paper ontology based on OWL which is new popular ontology language for semantic Web and represent the correlation among diverse paper properties as the DL(description logic) query, and then this system infers the correct results from the paper ontology by using the DL query and makes it possible to retrieve information intelligently. Finally, we compared our experimental result with the conventional retrieval.

• The Journal of Information Systems
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• v.18 no.1
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• pp.47-76
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• 2009

The economic growth that depended on IT industry is reaching to a limit. In order to overcome the limit, the convergence industry that makes new market and products is essential. However, companies preparing a jump into the convergence industry must understand the exact visions and characteristics of convergence. Therefore, we investigated the structural changes of industries caused by convergence and importance characteristics of convergence. Also, we demonstrated the current status of the convergence industry and analyzed economical, social/cultural, and technological environments that the companies are facing, and elaborated the opportunities of convergence. At last, we suggested basic requirements and strategies for companies starting a convergence business and IT utilization methods to accelerate the convergence business activation.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.358-360
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• 2000

컴포넌트는 소프트웨어 재사용 기술의 핵심 기술로서, 소프트웨어 개발 시간을 단축시키고 생산성을 향상시킨다. 인터넷의 급속한 보급과 컴포넌트 시장의 확산으로 컴포넌트 사용자들이 인터넷 상에서 검색, 저장, 유통하기 위하여 컴포넌트 명세가 정의되어야 한다. 컴포넌트 명세는 컴포넌트 특성을 명확히 이해하기 위하여 구문적(syntatic), 의미(semantec), 그들 사이의 관계, 사용 문맥, 품질 속성들을 포함한 정보가 기술되어야 한다. 본 논문에서는 컴포넌트를 명세하기 위한 명세 요소들을 살펴보며, 컴포넌트를 표현하기 위한 기술 방법들을 정의한다. 또한, 컴포넌트 메타데이터 및 리소스 정보, 외부 인터페이스들의 논리적 구조 및 시맨틱 표현기법을 연구하고 컴포넌트 명세서 표현을 위한 메타데이타 모델을 근거로 컴포넌트 명세서를 효과적으로 생성할 수 있는 XML 기반 컴포넌트 명세서 확장 모델을 개발하고자 한다.

• 한국IT서비스학회:학술대회논문집
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• 2007.05a
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• pp.155-160
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• 2007

현재의 우리나라 IT는 유비쿼터스화라는 커다란 변혁을 맞이하고 있다. 이에 물리공간에서는 하드웨어 중심의 편재된 유비쿼터스 컴퓨팅 또는 유비쿼터스 네트워크화가 진행되고 있다. 더불어 가상공간에서는 웹1.0의 한계를 뛰어넘는 웹2.0이 소개되었고 웹3.0으로의 진화를 모색하고 있다. 웹에서의 발전은 문맥을 추론하여 서비스를 할 수 있는 시맨틱 웹 서비스가 각광받을 전망이며 새로운 웹 서비스는 물리공간에서의 유비쿼터스화와 연계하여 분석하여야 기술발전의 트렌드를 이해할 수 있는 특징을 가지고 있다. 본 소고에서는 유비쿼터스화되는 웹에서의 차세대 기술인 웹3.0에 대한 소개와 이를 토대로 예상되는 웹 서비스 그리고 웹 서비스에 대한 보안을 살펴봄으로 다가올 미래 사회의 웹3.0 환경에서 안전하고 신뢰할 수 있는 웹 서비스가 구현되는 자료로 활용될 수 있을 것으로 기대한다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.58-61
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• 2010

유비쿼터스 센서 네트워크 환경에서 이기종 센서 간 상호 운용성을 높이기 위한 연구가 활발히 진행 중이다. 또한 스마트 모바일 기기의 보편화로 유비쿼터스 환경에 적합한 서비스들이 늘어나고 있다. 이러한 환경 속에서 스마트 모바일 기기를 사용하여 주변 센서에 접근하고 센서 데이터의 의미를 해석하여 사용자에게 제공한다면 센서의 활용을 극대화시킬 수 있다. 하지만 무선 센서는 센서 식별자와 센서 데이터만을 공급하기 때문에 센서의 종류와 측정 단위, 센서의 타입, 제조회사, 관리기관, 소유기관 등을 알 수 없을 뿐 아니라 어떤 센서로부터 데이터를 제공받고 있는지 인식할 수 없다. 따라서 이 논문에서는 무선 센서로부터 제공되는 센서 데이터를 사용자 및 관리자가 식별하고 이해할 수 있도록 센서 레지스트리를 설계한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.255-257
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• 2015

시맨틱 웹 기술 분야에서는 데이터를 온톨로지 형태로 표현함으로써 데이터의 의미를 인간뿐만 아니라 컴퓨터와 같은 기계도 이해할 수 있도록 한다. 이러한 온톨로지 데이터의 크기가 지속적으로 증가함에 따라 대용량 온톨로지 데이터 처리에 대한 필요성이 증가하고 있다. 이에 따라 본 논문에서는 대용량 온톨로지 데이터를 저장하고 질의를 할 수 있는 Hive 기반의 시스템을 제안한다. 또한 Hive에서 제공하는 파티셔닝을 이용하여 온톨로지 데이터에 대한 쿼리 반응 속도의 성능 향상을 위한 테이블 설계를 제안한다. 본 논문에서 제안하는 시스템의 성능 평가를 위하여 쿼리에 대한 반응 속도 측정을 수행한다.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.17-29
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• 2007

Inference engine that performs the brain of software agent in next generation's web with various standards based on standard language of the web, XML has to understand SWRL (Semantic Web Rule Language) that is a language to express the rule in the Semantic Web. In this research, we want to develop a forward inference engine, SMART-F (SeMantic web Agent Reasoning Tools-Forward chaining inference engine) that uses SWRL as a rule express method, and OWL as a fact express method. In the traditional inference field, the Rete algorithm that improves effectiveness of forward rule inference by converting if-then rules to network structure is often used for forward inference. To apply this to the Semantic Web, we analyze the required functions for the SWRL-based forward inference, and design the forward inference algorithm that reflects required functions of next generation's Semantic Web deducted by Rete algorithm. And then, to secure each platform's independence and portability in the ubiquitous environment and overcome the gap of performance, we developed management tool of fact and rule base and forward inference engine. This is compatible with fact and rule base of SMART-B that was developed. So, this maximizes a practical use of knowledge in the next generation's Web environment.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.111-124
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• 2011

The apartment' share of the housing has steadily increased and property assets have been valued in importance as the one of asset value. Information retrieval system using internet is particularly active in the real estate market. However, user satisfaction on real estate information system is not very high, and there is a lack of research on real estate retrieval to increasing efficiency until now. This study presents a new knowledge information system developed to consider region-related factor and individual-related factor in the real estate market. In addition it enables a real estate knowledge system to search various preferential requirements for buyers such as school district, living convenience, easy maintenance as well as price. We made a survey of the search condition preference of experts on 30 real estate agents and then analyzed the result using AHP methodology. Furthermore, this research is to build apartment ontology using semantic web technologies to standardize various terminologies of apartment information and to show how it can be used to help buyers find apartments of the interest. After designing architecture of a real estate knowledge information system, this system is applied to the Busan real estate market to estimate the solutions of retrieval through Multi-Attribute Decision Making(MADM). Based on the results of the analysis, we endowed the buyer and expert's selected factors with weights in the system. Evaluation results indicate that this new system is to raise not only the value satisfaction of user, but also make it possible to effectively search and analyze the real estate through entropy analysis of MADM. This new system is to raise not only the value satisfaction of buyer's real estate, but also make it possible to effectively search and analyze the related real estate, consequently saving the searching cost of the buyers.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.389-403
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• 2008

As the information of web dramatically increase, the existing web reveals more and more limitations in information search because web pages are designed only for human consumption by mixing content with presentation. In order to improve this situation, the Semantic Web comes on the stage by W3C. Semantic web is based on ontology that defines relationships between resources and it is enough to bring a significant advancement in web search. But to do this, the Semantic Web must provide a novel search and visualization methods which can make users instantly and intuitively understand why and how the results are retrieved because ontology has formal explicit descriptions of meaning. In this paper, we propose a semantic association-based search methodology that consists of how to find relevant information for a given user's query in the ontology, that is, a semantic network of resources and properties and how to provide proper visualization and navigation methods on the results. From this work, users can search the semantically associated resources for their query and also navigate such associations between resources.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.67-76
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• 2011

Recently, researches for semantic annotation methods which represent and search objects included in video data, have been briskly activated since video starts to be popularized as types for interactive contents. Different location data occurs at each frame because coordinates of moving objects are changed with the course of time. Saving the location data for objects of every frame is too ineffective. Thus, it is needed to compress and represent effectively. This paper suggests two methods; the first, ontology modeling for moving objects to make users intuitively understandable for the information, the second, to reduce the amount of data for annotating moving objects by using cubic spline interpolation. To verify efficiency of the suggested method, we implemented the interactive video system and then compared with each video dataset based on sampling intervals. The result follows : when we got samples of coordinate less than every 15 frame, it showed that could save up to 80% amount of data storage; moreover, maximum of error deviation was under 31 pixels and the average was less than 4 pixels.