• Journal of Korean Society of Archives and Records Management
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• v.20 no.1
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• pp.139-158
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• 2020

This study is the first paper to introduce in the country the preview of RiC-CM v0.2, the standard for the description of records based on archival principles by the ICA in December 2019, and an early stage of research that considers how to apply it at archive management. This study was conducted as follows. First, this study compared and analyzed entities, attributes, and relations of RiC-CM v0.1 and v0.2, and extracted the characteristics of version 0.2. Second, this study tried to confirm the semantic structure of the archives by constructing the ontology modeling in consideration of the basic principle and the extracted characteristics of version 0.2, and built ontology modeling using Protégé. Finally, this study figured out the differences from version 0.1 through entering individuals into Protégé and examined how the characteristics of version 0.2 was represented by ontology.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.206-216
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• 2007

With respect to the Semantic Web proposed to overcome the limitation of the Web, OWL has been recommended as the ontology language used to give a well-defined meaning to diverse data. OWL is the representative ontology language suggested by W3C. An efficient retrieval of OWL data requires a well-constructed storage schema. In this paper, we propose a storage schema construction technique which supports more efficient query processing. A retrieval technique corresponding to the proposed storage schema is also introduced. OWL data includes inheritance information of classes and properties. When OWL data is extracted, hierarchy information should be considered. For this reason, an additional XML document is created to preserve hierarchy information and stored in an XML database system. An existing numbering scheme is utilized to extract ancestor/descendent relationships, and order information of nodes is added as attribute values of elements in an XML document. Thus, it is possible to retrieve subclasses and subproperties fast and easily. The improved query performance from experiments shows the effectiveness of the proposed storage schema construction and retrieval method.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.38-45
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• 2004

The goal of this research is to develop a method of identifying a topic of a given text by looking at relationship of keywords defined in an ontology hierarchy. The keywords which are extracted from important sentences of the given text are mapped onto their correspond concepts which exist in the hierarchy. After all the words are mapped, the correspond concepts will be generalized into one single concept. The single concept will most likely be the topic of text. Our research have an approach that promotes both satisfaction in term of robustness and accuracy using ontologies and word frequency. So, this attempts are done in what they call as a hybrid approach. We try to take the challenge by using knowledge-statistical base approach. Experimental results show that proposed method outperforms the existing method using knowledge-base only.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.1
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• pp.101-127
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• 2018

The systematic management of research data is vital because it increases research data's value for research reproduction, verification, and reusability. Standard metadata will play a key role in research data registration, management, and data extraction. Research data has various structural relationships, such as research, research data, data sets, and files, and associated with entities such as citations and research results. The study proposes an ontology model for research data management. It also suggests the application of ontology to NTIS. Previous studies, metadata standard analyses, and research data repository case studies were conducted.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.247-256
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• 2008

This research is to develop product retrieval system through simplified communication by applying intelligent agent technology based on automatically created domain ontology to present solution on problems with e-commerce system which searches in the web documents with a simple keyword. Ontology development extracts representative term based on classification information of international product classification code(UNSPSC) and jewelry websites that is applied to analogy relationship thesaurus to establish standardized ontology. The intelligent agent technology is applied to retrieval stage to support efficiency of information collection for users by designing and developing e-commerce system supported with semantic web. Moreover, it designs user profile to personalized search environment and provide personalized retrieval agent and retrieval environment with inference function to make available with fast information collection and accurate information search.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.147-158
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• 2019

The Korean food, which has been attracting attention only as a unique culture of Korea, has become popular in the world market by being used as a material of Korean Wave and me-media. The systematic organization of knowledge for recipes and related information can highlight the value of Korean food. It will serve as a basis for improving the reusability of Korean food contents through expanded and limited search and effective browsing. This study purports to design an ontology for establishing Korean food knowledge structure. Ontology modeling is based on OWL. Vocabularies of Korean food were examined based on 32 volumes of Korean food information, and data elements were extracted by analyzing five domains and applications. As a result, the study derived classes and properties, and proposed an indexing example.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.96-100
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• 2008

An ontology provides an explicit specification of concepts and relations on information extracted from database or on human knowledge. Using an ontology, The information can be reconstructed according to semantic relations. In this paper. IT-People Event Ontology is constructed using people information extracted from web portals. IT-People Event Ontology represents constant information and time-temporal information on people. A system using this ontology outputs the well-organized reconstructed information on a specific individual in interest, and then the reconstructed information is suitable for users' demand.

• Journal of Digital Contents Society
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• v.17 no.2
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• pp.81-88
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• 2016

The general frequent pattern mining considers frequency and support of items. To extract useful information, it is necessary to consider frequency and weight of items that reflects the changing of user interest as time passes. The suitable services considering time or location is requested by user so that the weighted mining method is necessary. We propose a method of weighted frequent pattern mining based on service ontology. The weight considering time and location is given to service items and it is applied to association rule mining method. The extracted rule is combined with stored service rule and it is based on timely service to offer for user.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.348-353
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• 2008

이미지의 사용이 증가함에 따라 이미지 중 사용자가 원하는 이미지를 효율적으로 검색하기 위한 방법들이 연구되어 왔다. 본 논문에서는 질의 이미지를 분석하여 이미지 특징(feature)을 추출한 후 이미지 특징에 대한 유사도 평가를 통한 이미지 검색 및 온톨로지를 기반으로 검색된 이미지들과 유사하다고 판단된 이미지와 그러한 이미지들의 의미적 정보를 추출하는 방법을 제안한다. 제안된 시스템은 질의 이미지에서 색상, 질감, 모양 등의 특징을 추출하여 유사도 평가를 통해 검색된 이미지를 제공하고, 내용기반 이미지 검색 방식을 통해 이미지를 검색하고, 온톨로지를 이용해 이미지의 의미적 정보를 추출하여 사용자에게 이미지와 관련된 의미적 정보를 제공한다.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.479-486
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• 2005

The ontology was proposed to construct the logical basis of semantic web. Ontology represents domain knowledge in the formal form and it enables that machine understand domain knowledge and provide appropriate intelligent service for user request. However, the construction and the maintenance of ontology requires large amount of cost and human efforts. This paper proposes an automatic ontology construction method for defining relation between concepts in the documents. The Proposed method works as following steps. First we find concept pairs which compose association rule based on the concepts in domain specific documents. Next, we find pattern that describes the relation between concepts by clustering the context between two concepts composing association rule. Last, find generalized pattern name by clustering the clustered patterns. To verify the proposed method, we extract relation between concepts and evaluate the result using documents set provide by TREC(Text Retrieval Conference). The result shows that proposed method cant provide useful information that describes relation between concepts.