• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.613-614
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• 2006

Design data, information, and knowledge have complex associations with each other. Systems related with the management of the data, information, and knowledge are various, and the representations are numerous. Therefore it is difficult to construct a knowledge based design system with a full association knowledge for supporting the design tasks. In this research, OWL based ontology model for an excavator design is developed for the representation of the relationships. Also an ontology model is used to develop the knowledge based excavator design system.

• 한국도서관정보학회지
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• 제37권2호
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• pp.191-216
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• 2006

본 연구에서는 선행 연구를 근거로 온톨로지에 대한 정의와 기능 그리고 종류에 대해 기술하였으며, 특히 온톨로지의 자동 구축을 위한 어휘인 OWL(Ontology Web Language)에 대하여 어휘와 구문 사용방법에 대하여 기술하였다. 또한 OWL의 구문 및 기능에 대한 사용법을 쉽게 익힐 수 있도록 클래스(Class), 속성(Property), 클래스간의 관계, 속성간의 관계 등에 대하여 각 구문에 대한 상세한 정의와 함께 기 구축된 Wine 온톨로지를 근거로 사용사례와 그 설명을 제시하였다.

• 디지털산업정보학회논문지
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• 제9권3호
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• pp.39-48
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• 2013

Ontology has an important role in semantic web to construct and query semantic data. When system make changes to ontologies, questions arise about versioning of these changes. Applying this changes on a dynamic environment is even more important. To apply these changes, change specification method is needed. Early studies show RDF-based syntax for the operations between old and new ontologies. When several ontology versions can be used for some query, if possible, using possible newest version ontology with prospective use is best way to process the query. Prospective use of ontology means using a newer version of an ontology with a data source that conforms to a more recent ontology. In this paper, for prospective use of ontology version, structure of change specification of class and property through several ontology versions is proposed. From this, efficient adaptive ontology version selection for a query can be possible. Algorithm for structure of version transition representation is proposed and simulation results show possible newest version number for queries.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• 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.

• 한국IT서비스학회지
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• 제12권1호
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• pp.323-340
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• 2013

As the importance of collaboration becomes critical in today's open and complex business environment network, the issues and solutions on compatibility and reusability between different kinds of applications are being increasingly important as well in systems analysis and design. And therefore, service-centered SOA is receiving attention in such business environment as a strategic approach that makes possible for prompt action according to the needs of users and business process. Various implementation methodologies have been proposed for SOA, however, in practical aspects most of them have some problems since they fail to propose specific policies in definition and identification of services for the exact user requirements and business situations. To solve or alleviate those problems, this paper suggests a new service identification model based on hierarchical ontology, where three different ontologies such as business ontology, context ontology and service ontology are proposed to define the relationship and design the link between user requirements, business process, applications and services. Through a suggested methodology in this paper, it would be possible to provide proactive services that meets a variety of business environments and demands of user. Also, since the information can be modified adaptively and dynamically by hierarchical ontology, this study is expected to play a positive role in increasing the flexibility of systems and business environments.

• 한국산업정보학회논문지
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• 제9권1호
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• pp.17-23
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• 2004

본 논문은 한국어정보처리에서 단어의 의미를 결정하기 위한 말뭉치 기반의 온톨로지 학습 방법을 제시하고 있다. 먼저 이미 확보된 전자사전의 정보를 이용하여 단어의 확실한 의미를 우선 결정한 후, 아직 결정하지 못한 단어의 의미는 온톨로지를 이용하여 최종 결정하는 절차를 거친다. 온톨로지를 단어 의미 중의성 해소를 위한 지식베이스로 사용하기 위해서는, 온톨로지 내 개념들간의 상호정보가 말뭉치의 통계 정보에 근거하여 미리 계산된다. 계산된 상호정보 값을 가중치로 간주하면 온톨로지는 가중치 그래프로 생각할 수 있으므로, 개념간 최소 경로를 통하여 개념간 연관도를 알아 볼 수 있다. 실제 기계번역 시스템에서 본 방법은 온톨로지를 사용하지 않은 방법보다 9％의 성능 향상을 가져오는 결과를 얻을 수 있었다.

• 한국한의학연구원논문집
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• 제17권2호
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• pp.57-62
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• 2011

We in this paper propose a semantic search system using the basic ontology in Korean medicine field. The basic ontology provides a formalization of medicinal materials, formulas, and diseases of Korean medicine. Recently, many studies for the semantic search system have been proposed. However, they do not support the semantic search and reasoning in the domain of Korean medicine because they do not have the Korean medicine ontology. Our system provides the semantic search features of semantic keyword recommendation, associated information browsing, and ontology reasoning based on the basic ontology. In addition, they also have the features of ontology search of a form of table and graph, synonym search, and external Open API supports. The general search engines usually provide search results for the simple keyword, while our system can also provide the associated information with respect to search results by using ontology so that can recommend more exact results to users.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2003년도 종합학술대회 논문집
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• pp.197-203
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• 2003

The purpose of the study is to develop an integrated knowledge structuring system for the domain of engineering, in which ontology-based literature mining, knowledge acquisition, knowledge integration, and knowledge retrieval are combined using XML-based tag information and ontology management. The system supports combining different types of databases (papers and patents, technologies and innovations) and retrieving different types of knowledge simultaneously. The main objective of the system is to facilitate knowledge acquisition and knowledge retrieval from documents through an ontology-based dynamic similarity calculation and a visualization of automatically structured knowledge. Through experimentations we conducted using 100,000 words economic documents reported in the "Go！ Japan" project for analyzing Japanese industrial situation, and 100,000 words molecular biology Papers, we show the system is Practical enough for accelerating knowledge acquisition and knowledge discovery from the information sea.

• 한국컴퓨터정보학회논문지
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• 제22권6호
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• pp.69-77
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• 2017

The information related to legislation is massive, and it takes much time and effort to manually build the legislation ontology. Thus, studies on machine-based automated building methods are underway. However, the studies to automatically construct such systems focus on using TBox construction, and those based on automated ABox construction, which corresponds to instances, theoretical systems and data building cases, has not yet been sufficiently developed. Therefore, this paper suggests using a semi-automatic ABox construction method based on sentence patterns to automatically build the ontology for the legislation of the Republic of Korea. Precision and Recall experiments were conducted to further discuss the performance of the suggested method. These experiments provide a comparison between the manual classification, and the triples built by the machines of the legal information by assessing the corresponding numerical values.