• 지능정보연구
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• 제14권4호
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• pp.69-87
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• 2008

이제 인터넷은 시맨틱 웹(Semantic Web)의 형태로 진화 발전하고 있다. 그 결과 시맨틱 웹의 지식을 표현하는 백본 인 온톨로지가 매우 중요하게 인식되고 있다. 그러나 온톨로지를 구축하는 것은 많은 시간과 자원을 필요로 하는 작업이다. 이로 인해 온톨로지 추출도구(ontology extraction tool)에 대한 개발의 필요성이 지난 십여 년간 제기되어 왔으며, 온톨로지를 자동으로 추출하거나 온톨로지 구축을 돕는 도구들이 개발되었다. 그러나 여러 온톨로지 자동추출도구들 중에 구축하고자 하는 온톨로지의 사용자 요구사항에 적합한 자동추출도구를 선택하기 위해서는 이런 도구들에 대한 평가지표가 필요하다. 하지만, 현재 이런 도구들을 평가하기 위한 포괄적인 평가 프레임워크(comprehensive evaluation framework)가 존재하지 않는다. 본 연구에서는, 문헌연구를 수행하여 온톨로지 자동추출도구가 갖춰야 할 핵심 요소들을 찾고, 온톨로지 추출도구들을 평가하기 위한 일련의 평가지표들을 개발했다. 또한 본 연구에서 제안하는 평가지표에 따라 온톨로지 자동추출도구인 OntoLT, Text-To-Onto, TERMINAE, OntoBuilder를 평가해 보았다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• 한국컴퓨터정보학회논문지
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• 제14권6호
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• pp.17-26
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• 2009

국방 분야에서 기존에 구축된 정보시스템은 대부분 대용량의 정보처리 등 단순한 정보처리 중심이었기 때문에 정보의 지적인 수행 능력이나 지식의 표현기술에 대한 능력은 부족한 실정이다. 따라서 기존의 국방정보시스템이 효율적 정보검색 및 관리를 가능케 하는 지능형 국방정보시스템으로 변화되기 위해서는 지식 구축의 핵심이 되는 국방 온톨로지 구축이 필수적이다. 본 논문에서는 6단계 상향식 방법을 이용한 온톨로지 추출 방안을 기술하고, 이를 국방교육훈련 분야에 적용하여 국방 온톨로지 프로토타입을 추출한 후 대표적인 온톨로지 개발 툴인 $Prot\acute{e}g\acute{e}$를 이용하여 구현하였다.

• 한국인터넷방송통신학회논문지
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• 제9권3호
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• pp.61-67
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• 2009

인터넷의 발달로 전자문서가 증가함에 따라, 정보검색기술의 중요성도 함께 증가하게 되었다. 본 연구는 비정형 텍스트 웹 문서로부터 사용자가 요구하는 핵심 의미 지식을 추출하기 위하여 LGG(Local Grammar Graph) 구축에 기반 하여 보다 효율적이고 정확한 지식구축을 가능하게 한다. 주가등락이라는 특정 분야의 패턴을 추출하여 만든 패턴 문법을 사용해서 OWL(Web Ontology Language) 기반의 온톨로지를 구축하였다. 특정 분야의 온톨로지를 구축함으로써 기존 검색에서 할 수 없었던 지식의 의미 검색이 가능하며 나아가 사용자가 원하는 질의에 대한 정보의 추론이 가능할 것이다.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.317-322
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• 2021

The modern technological era has brought about the Semantic Web. Ontologies are essential to achieve the vision of the Semantic Web. Ontologies enable machines to understand data. The Arabic Language currently does not have a significant presence on the Web. To achieve a comparable level of Arabic access to other important languages, further work is needed to build Arabic ontologies. A goal is to design and create a robust Arabic ontology that represents the concepts from a large and significant subset of Arabic. We use a source of Hadiths (prophet saying and deeds) from Riyadh As-Saliheen. Preliminary results are very promising.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2005년도 e-Biz World Conference 2005
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• pp.55-61
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• 2005

We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2002년도 제1차워크샵
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• pp.25-33
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• 2002

Recent developments in literature data mining for biology call for the design of a common framework that can be used to assess the performance of the reported systems in a fair and objective way. In this talk, we present an on-going effort to make it possible, in the form of challenges in the extraction of biological pathways and in the ontology construction. We are currently making this effort jointly with Lynette Hirschman (MITRE), Junichi Tsujii (University of Tokyo), Limsoon Wong (KRDL), and Cathy Wu (Georgetown University)

• 한국지능시스템학회논문지
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• 제17권3호
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• pp.291-296
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• 2007

최근에 여러 분야에서 구축되고 있는 온톨로지는 기계가 이해할 수 있는 지식을 축적하는 것을 목표로 하고 있다. 기계가 온톨로지를 이용하여 정보의 관리 및 해석을 스스로 하는 것이 가능할 것으로 본다. 본 논문에서는 온톨로지의 인스턴스를 구성하는 속성을 기존 웹 문서의 구조정보로부터 추출하는 알고리즘을 제안하였다. 특히, 속성 정보로 구성하는 도메인 지식을 계층화함으로써 속성 추출 알고리즘을 개선하고, 추출 결과의 품질을 향상시킨다. 2만 문서를 대상으로 제안된 알고리즘을 적용한 결과 약 83%의 신뢰도의 속성 정보를 추출할 수 있었다.

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.754-759
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• 2007

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

• Journal of Information Technology Applications and Management
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• 제26권1호
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.