• Journal of the Korean Society for Library and Information Science
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• v.42 no.1
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• pp.193-211
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• 2008

The purpose of this study is to examine semantic interoperability in terms of metadata elements and content designation in context of digital libraries. This study analyzed 78 digital libraries implemented using Greenstone application with respect to metadata elements and their content designation. Using crosswalks of digital libraries' metadata elements, and comparisons of content designation in elements. this study identifies three aspects which can impact semantic interoperability. First, there were less than 25% core metadata elements even within homogeneous information communities. Second, discrepancy exists between element names and their usage. Third, different levels were identified when assigning content to designated elements in terms of integrity and completeness.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.3
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• pp.428-437
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• 2018

This study derives evaluation terms by analyzing the semantic relationship between design elements and sentiment terms in regards to fashion design. As for research methods, a total of 38,225 texts from Daum and Naver Blogs from November 2015 to October 2016 were collected to analyze the parts, frequency, centrality and semantic networks of the terms. As a result, design elements were derived in the form of a noun while fashion image and user's emotional responses were derived in the form of adjectives. The study selected 15 noun terms and 52 adjective terms as evaluation terms for men's striped shirts. The results of semantic network analysis also showed that the main contents of the users of men's striped shirts were derived as characteristics of expression, daily wear, formation, and function. In addition, design elements such as pattern, color, coordination, style, and fit were classified with evaluation results such as wide, bright, trendy, casual, and slim.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.318-326
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• 2004

The ebXML (Electronic Business using eXtensible Markup Language) Specification Schema is to provide nominal set of specification elements necessary to specify a collaboration between business partners based on XML. As a part of ebXML Specification Schema, BPSS (Business Process Specification Schema) has been provided to support the direct specification of the set of elements required to configure a runtime system in order to execute a set of ebXML business transactions. The BPSS is available in two stand-alone representations, a UML version and an XML version. Due to the limitations of UML notations and XML syntax, however, current ebXML BPSS specification is insufficient to specify formal semantic constraints of modeling elements completely. In this study, we propose a classification schema for the BPSS semantic constraints and describe how to represent those semantic constraints formally using OCL (Object Constraint Language). As a way to verify a Business Process Specification (BPS) with the formal semantic constraint modeling, we suggest a rule-based approach to represent the formal constraints and to use the rule-based constraints specification to verify BPSs in a CLIPS prototype implementation.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.345-369
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• 2022

The purpose of this study is to build a metadata set based on the semantic structure of the humanities field research articles for research data that can associate research data and research articles. To understand the interest of Humanities researchers, keywords of research articles were categorized. By proceeding the keywords classification and analyzing based on the semantic structure of general research papers, additional elements to be added were identified for reflecting the characteristics of the humanities field. Based on it, 17 metadata elements based on the semantic structure of research papers in the humanities field was determined. In order to evaluate whether the metadata is appropriate as a metadata for research data in the humanities field, a survey was conducted on researchers in the humanities field. As a result of the survey, 7 elements were judged to be suitable for use as metadata for research data in the field of humanities, and 10 other elements were identified as usable elements. Drawing on the survey results, the metadata based on the semantic structure of the humanities field research articles for research data was constructed.

• Journal of the Korean Society for information Management
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• v.17 no.1
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• pp.21-47
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• 2000

Keeping the semantic interoperability between different formats is very important for reuseing and consistently processing metadata. This article is to design common schema and KORMARC schema based on RDF schema. For this, common elements are made by comparison of Dublin Core elements and KORMARC fields. The schema of these elements is designed for construction of semantic interoperability, basing RDF schema specification and syntax specification. Eventually, the semantic interoperability between a number of metadata formats can be constructed by matching the common elements to each attribute of format. KORMARC schema is designed by the application of common schema.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.1
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• pp.227-243
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• 2017

This study proposed a structural and semantic framework for the characterization of events and segments in Web videos that permits content-based searches and dynamic video summarization. Although MPEG-7 supports multimedia structural and semantic descriptions, it is not currently suitable for describing multimedia content on the Web. Thus, the proposed metadata framework that was designed considering Web environments provides a thorough yet simple way to describe Web video contents. Precisely, the metadata framework was constructed on the basis of Chatman's narrative theory, three multimedia metadata formats (PBCore, MPEG-7, and TV-Anytime), and social metadata. It consists of event information, eventGroup information, segment information, and video (program) information. This study also discusses how to automatically extract metadata elements including structural and semantic metadata elements from Web videos.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.83-92
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• 2007

Semantic libraries can be used for EDI messages to exchange by implementing the semantic dictionaries. This paper describes the design information of semantic libraries for the field engineers to implement the semantic dictionary using metadata. The components of semantic libraries are semantic elements, semantic units and mapping tables. The basic characteristics and design methods related implementing are proposed. Also the metadata semantic dictionaries including the components and rules are introduced.

• Journal of KIBIM
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• v.11 no.3
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• pp.22-33
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• 2021

In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.513-525
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• 2006

Search results of XML keyword search are defined generally as the most specific elements containing all query keywords in the literature. The labels of XML elements and semantic information such as ontology, conceptual model, thesaurus, and so on, are used to improve the preciseness of the search results. This paper presents a hierarchical index for an efficient XML keyword query processing on the condition that returnable search concepts are defined and users' query concepts can be interpreted with the help of the semantic information. The hierarchical index separately stores the XML elements containing a keyword on the basis of the hierarchical relations of the concepts that the XML elements belong to, and makes it possible to obtain least common ancestors, which are candidates for the search results, with selectively reading the elements belonging to the concepts relevant to query concepts and without considering all the combinations of the elements having been read. This paper deals with how to organize the hierarchical index and how to process XML keyword queries with the index. In our experiment with the DBLP XML document and the XML documents in the INEX2003 test set, the hierarchical index worked well.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.752-759
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• 2022

The instantiation of spaces as a discrete entity allows users to utilize BIM models in a wide range of analyses. However, in practice, their utility has been limited as spaces are erroneously entered due to human error and often omitted entirely. Recent studies attempted to automate space allocation using artificial intelligence approaches. However, there has been limited success as most studies focused solely on the use of geometric features to distinguish spaces. In this study, in addition to geometric features, semantic relations between spaces and elements were modeled and used to improve space classification in BIM models. Graph Convolutional Networks (GCN), a deep learning algorithm specifically tailored for learning in graphs, was deployed to classify spaces via a similarity graph that represents the relationships between spaces and their surrounding elements. Results confirmed that accuracy (ACC) was +0.08 higher than the baseline model in which only geometric information was used. Most notably, GCN was able to correctly distinguish spaces with no apparent difference in geometry by discriminating the specific elements that were provided by the similarity graph.