• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.75-94
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• 2010

In the current information environment, metadata interoperability has become the predominant way of organizing and managing resources. However, current approaches to metadata interoperability focus on the superficial mapping between labels of metadata elements without considering semantics of each element. This research applied facet analysis to address these difficulties in achieving metadata interoperability. By categorizing metadata elements according to these semantic and functional similarities, this research identified different types of facets: basic, conceptual, and relational. Through these different facets, a faceted framework was constructed to mediate semantic, syntactical, and structural differences across heterogeneous metadata standards.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.353-360
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• 2004

World Wide Web is not more meaningless sea of information but is becoming the Semantic Web that provides many users with meaningful information. The starting point is the XML and metadata, RDF is a stopover which gives technique to relate arbitrary web resources. And now, the semantic and logic of web resources can be settled in the Ontology. A lot of educational multimedia web resources in Korea have produced their metadata with KERIS's KEM(Korea Educational Metadata). Therefore our country have to start the study of the semantic and logic in web resources. But, many researchers in Korea are more eager to study Dublin Core's DC and SCORM's LOM metadata specification than KEM. Thus the study of method about sharing and integrating these three metadata specifications should be performed before the study of semantic and logic in web resources in Korea. We design the Ontology to integrate these three metadata specifications and implement the prototype system using this Ontology. These three metadata have some elements that have same labels and meanings, and other elements have different labels and same meanings. To match these different labels which have same meanings, we adapted the one-to-one mapping technique in designing our Ontology. This designed Ontology was imported as "integrated schema" in our prototype searching system to integrate three different metadata in databases. Moreover we know that the more specific property design of class in Ontology was needed in order to provide users with more informed searching results such as synonym, antonym, hierarchy and associations.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.298-319
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• 2002

The Semantic Web is a new technology that attempts to achieve effective retrieval, automation, integration, and reuse of web resources by constructing knowledge bases that are composed of machine-readable definitions and associations of resources that express the relationships among them. To have this kind of Semantic Web in place, it is necessary to have the following infrastructures: capability to assign unchangeable and unique identifier (URI) to each resource, adoption of XML namespace concept to prevent collision of element and attribute names defined by various institutions, widespread use of RDF to describe resources so that diverse metadata can be interoperable, use of RDF schema to define the meaning of metadata elements and the relationships among them, adoption of DAML+OIL that is built upon RDF(S) to increase reasoning capability and expressive power, and finally adoption of OWL that is built upon DAML+OIL by removing unnecessary constructors and adding new ones based on experience of using DAML+OIL. The purpose of this study is to describe the central concepts and technologies related to the Semantic Web and to discuss the benefits of metadata interoperability based on XML/RDF schemas and the potential applications of diverse ontologies.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.1-13
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• 2016

The many researches on context-aware service based on the combination of semantic technology and IoT environment are being actively done. However, the previous study exploiting ontology has limitations not to accommodate the service requirement changes due to ontology prebuilt by specific service scenario. Although the concept of cross vertical ontology has emerged in order to overcome the limitation, it has other limitations that need additional components composing service environment for expressing context information and can't represent state information of environment elements. To cope with these limitations, we propose SISO (Semantic-based IoT Service Ontology) that can represent the states of environmental element without the need for additional context-information element. To verify SISO's characteristics, we select the service scenario and present applied results. The qualitative analysis comparing with the previous study is also presented by the applied results of service scenario.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.1
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• pp.135-147
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• 2016

The purpose of this research is to study the semantic characteristics of outdoor brand names by analyzing 94 brand names in domestic market, so as to propose ways to develop strategic brand names. The results are as follows. When it comes to outdoor brand products, the emphasis is placed on their functional features. Thus, the majority of outdoor brands surveyed in this Study were using strategic descriptive brand names which clearly denote the properties and effects of the relevant products to leave lasting impressions on consumers'minds. In other words, the outdoor brands surveyed herein were using brands which inform consumers of the specific business and product categories, express the concept of the brands, and provide them with information on the features and benefits of the products such as high quality, high-class, and luxurious lifestyle. In conclusion, the components of outdoor brand names are crucial elements which symbolize the concepts, functions or features of the relevant brands. In order to develop brand names consisting of components which build brand powers and enhance brand images, it is imparetive to develop more unique and characteristic brand names.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.2
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• pp.135-152
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• 2003

With the rapid growth of the Internet, digital contents have increased in a geometric progression and the types also became much varied. In order to make it easier to identify and search digital contents on the Internet, which is basically a distributed network environment, it is essential to organize and manage metadata. In this study, we have comparatively analyzed the data elements of the meta data formats currently approached from different aspects in diverse fields, so as to provide basic materials for securing interoperability of the meta data formats. We selected Dublin Core, Semantic Header, MARC, IAFA Templates, and TEI Header as the general metadata formats of digital contents used widely in all areas, and we carried out comparisons and analyses based on the literature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.277-288
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• 2021

Building information modeling (BIM) element to industry foundation classes (IFC) entity mappings need to be checked to ensure the semantic integrity of BIM models. Existing studies have demonstrated that machine learning algorithms trained on geometric features are able to classify BIM elements, thereby enabling the checking of these mappings. However, reliance on geometry is limited, especially for elements with similar geometric features. This study investigated the employment of relational data between elements, with the assumption that such additions provide higher classification performance. Neural structured learning, a novel approach for combining structured graph data as features to machine learning input, was used to realize the experiment. Results demonstrated that a significant improvement was attained when trained and tested on eight BIM element types with their relational semantics explicitly represented.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.348-357
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• 2002

This paper discusses constraints on grammaticalization, a primarily diachronic process through which lexical elements take on grammatical functions. In particular, it will argue that two constraints on this process, namely Persistence and Lwering, explain the different distributional patterns of time-relationship adverbs in Japanese, Korean, English and German. Furthermore, it will suggest that the distributional difference between Japanese and Korean time-relationship adverbs is not an isolated phenomenon but is a reflection of the overall semantic typological differences between the two languages in the sense of Hawkins (1986).

• Journal of Information Technology Services
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• v.7 no.3
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• pp.271-286
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• 2008

The core of the semantic web is ontology, which supports interoperability among semantic web applications and enables developer to reuse and share domain knowledge. It used a variety of fields such as Information Retrieval, E-commerce, Software Engineering, Artificial Intelligence and Bio-informatics. However, the reality is that various errors might be included in conceptual hierarchy when developing ontologies. Therefore, methodologies and supporting tools are essential to help the developer construct suitable ontologies for the given purposes and to detect and analyze errors in order to verify the inconsistency in the ontologies. In this paper we propose a new approach for ontology error detection based on the Concept Lattices of Formal Concept Analysis. By using the tool that we developed in this research, we can extract core elements from the source code of Ontology and then detect some structural errors based on the concept lattices. The results of this research can be helpful for ontology engineers to support error detection and construction of "well-defined" and "good" ontologies.