• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.109-111
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• 2004

시맨틱웹의 실용화에 대한 연구가 활기를 띠면서 국내에서도 시맨틱웹에 관한 연구와 그 기반이 되는 온톨로지에 대한 관심이 높아지고 있다. RDF, DAML+OIL 등 많은 온톨로지 언어가 개발되었고 W3C는 2004년 2월 OWL(Web Ontology Language)을 온톨로지를 위한 표준 언어로 발표했다. 이와 함께 프로티지 등 온톨로지 개발을 위한 편짐 도구들에 관한 연구도 진행되고 있다 본 논문에서는 기존 편집기의 문제를 지적하고 새로운 편집 방법을 통한 온톨로지 편집기를 개발하였다. 이 편집기는 가장 널리 사용되고 있는 온톨로지 개발도구인 프로티지와 그 위에서 작동하는 OWL plug-in을 기반으로 한다.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.881-888
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• 2005

As the internet continues to grow, the quantity of information on the Web increases beyond measure. The internet users' abilities and requirements to use information also become varied and complicated. Ontology can describe correct meaning of web resource and relationships between web resources. And it can extract conformable information that a user wants. Accordingly, we need the ontology to represent knowledge. W3C announced OWL(Web Ontology Language), a meaning description technology for such web resources. But, the development of a professional use of tools that can compose and edit effectively is not yet developed adequately. In this paper, we design and implement an Ontology editor which generates and edits OWL documents through intuitional interface, with a OWL parser, a Internal DataModel, and a Serializer.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.511-520
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• 2013

Recently, human activities have expanded from outdoor spaces to indoor spaces since a lot of complex buildings were constructed over the world. Especially, visitors in a shopping mall would like to receive specific information of interest regarding various shopping-related activities as well as shopping itself. However, when it comes to providing the information, existing guide services have some drawbacks. Firstly, the existing services cannot provide visitors with the information of other stores simply and promptly on the current location. Secondly, the services have difficulties in representation and share of the shopping-related knowledge, and in providing inferred information. Thus, the purpose of this study is to develop a method that allows topological analysis utilizing ontology technique around the current position in such shopping mall in order to provide shopping-related information. For this, the shopping activity ontology model is designed, and based on the ontology model, inferencing rules are defined in order to extract the information of interest efficiently through semantic queries. Also, a geocoding method in indoor spaces is used regarding the current location, and optimal routing analysis, which is one of topological analysis, is applied with the result from the semantic queries. As a result, an Android application is developed for 3D visualization and user interface.

• The Journal of Korean Association of Computer Education
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• v.13 no.5
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• pp.29-38
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• 2010

In this study we developed an ontology-based e-learning system for supporting self-directed learning. In this system, a domain ontology of a learning topic was constructed and relation properties were defined to indicate the relations among the learning concepts. The learning concepts and their relationships are structured visually through the domain ontology. It also boosts understandabilities of students by means of the visualization of relationships among the pre and post concepts. In addition, the system provides reasoning so that learners can do intelligent query when they want to learn more or they are curious about the high-level knowledge while they are learning a topic. These features of the system would help learners' self-directed and active learning.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.185-192
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• 2013

The purpose of this study is to set the relationship between each parts that forms the engine of an automobile based on the 3D visualization technology which is able to be learned according to the skill of the operator in the industry field and to recommend the auto parts using a task ontology. A visualization method was proposed by structuring the complex knowledge by signifying the link and the node in forms of a network and using SOM which can be shown in the form of 3 dimension. In addition, by using is-a Relationship-based hierarchical Taxonomy setting the relationship between each of the parts that forms the engine of an automobile, to allow a recommendation using a weighted value possible. By providing and placing the complex knowledge in the 3D space to the user for an opportunity of more realistic and intuitive navigation, when randomly selecting the automobile parts, it allows the recommendation of the parts having a close relationship with the corresponding parts for easy assembly and to know the importance of usage for the automobile parts without any special expertise.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.777-784
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• 2017

In the architectural space, the user's behavior is the most important factor in evaluating the quality of architecture. Normally, the evaluation of user behavioral performance was carried out after a building was completed. Recently, interest in and efforts at pre-simulation based on information technology are accelerating. However, since existing user simulation technology is concerned mainly with simply escaping from a large space, it is impossible to simulate the behavior of multiple users in an architectural space. The present study strives to develop a human-figured intelligent agent for advanced user simulation based on ontology. The main purpose of the study is to employ the intelligent behaviors of a NPC(Non-player Character) to infer the ontology of both spatial and user information. In this paper, we intend to integrate ontology inference technology into the virtual space. And also, this study suggest the ontology visualization technology which illustrate the ontology-based information and their change in the spatial information.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.390-394
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• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.703-717
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• 2006

The Semantic Web has the objective of developing universal media in which machine-processable semantic information can be represented and shared, and it is therefore important to distribute ontologies that represent this kind of semantic information to the Web and make them available to multiple parties. However, the current ontology authoring tools are not operating on the Web, which makes it difficult to distribute ontologies directly to the Web and to create and edit them collaboratively with other people. This paper proposes a framework that facilitates the ontology construction and sharing, realizing easy distribution of ontologies to the Web. Wiki is one of the frameworks for collaborative construction and sharing of knowledge on the Web, and Wiki contents consist of natural language texts and simple markup language for visualization. For better collaboration in creating and sharing ontologies, this paper suggests the Semantic Wiki that embodies the Semantic Web features to the existing Wiki system. The Semantic Wiki framework facilitates the collaboration in ontology co-authoring and sharing for people, and at the same time, makes it possible for the agent software to easily manage the ontology information. Eventually, the Semantic Wiki system accomplishes various tasks including the semantic view, the semantic navigation, and the semantic query.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.251-260
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• 2016

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patent, and project reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer the further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a RDB-to-Triples transformer is implemented. Lastly, we show an experiment on R&D data integration using the lightweight ontology, triples generation, and visualization and navigation of the knowledge map.