• Title/Summary/Keyword: semantic metadata

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Study on the Semantic Extension of the Concept of Metadata (메타데이터의 의미론적 확장에 관한 연구)

  • Nam, Tae-Woo;Lee, Seung-Min
    • Journal of the Korean Society for Library and Information Science
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    • v.44 no.4
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    • pp.373-393
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    • 2010
  • In the current information environment around the library community, metadata is recognized as a sophisticated and powerful tool that can manage and represent information resources. However, with the discreet use of the concepts of metadata and metadata standard, there is no clear boundary that differentiates metadata standard from simple resource description and traditional bibliographic structure, leading to confusion as to what a metadata and metadata standard is. To consider these issues, this research discussed what metadata and metadata standards are based previous definitions of metadata. Based on those definitions, the fundamental concept of metadata is reestablished to be properly used in the library community.

A Study on Designing with RDF for manage of Web Service Metadata (웹 서비스 메타데이타 관리를 위한 RDF 설계에 관한 연구)

  • 최호찬;유동석;이명구;김차종
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.623-625
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    • 2003
  • The Semantic Web stands out in the next generation web, recently. In the Semantic Web, any information resources is defined by semantics and semantic links is given among these. It is different from existing web service environment. RDF (Resource Description Framework) is the data model to describe metadata of web resource and is to support for semantic links. And it is much the same as WSDL (Web Serice Description Language). In theis paper, we propose the RDF design method to improve the search performance by integrating RDF data unit with WSDL. We confirm the performance and efficiency of search will be improved by using the proposed method.

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A Method for build an Ontology-based Component Semantic Search System for Reconfiguration of Weapon System (무기체계 재구성을 위한 온톨로지 기반 컴포넌트 시맨틱 검색 시스템 구축 방법)

  • Seo, Dong Jin;Seo, Yoonho
    • Journal of the Korea Society for Simulation
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    • v.25 no.1
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    • pp.11-20
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    • 2016
  • Recently in the field of defense Modeling and Simulation (M&S), Component-Based Development technology is widely applying to save the cost and increase the reusability of weapon system development. Related with this, researches for rapid reconfiguration and simulation of the component-standardized weapon system is actively carrying out. To rapidly reconfigure the new weapon system, complex and various functions of component information has to be effectively searched. So, it requires differentiated search technique unlike existing Keyword-based Search method. Semantic Search System provides semantically related information among the extensive information. In this research, metadata of weapon system components and their representative functional words are built as an ontology. And it provides an ontology-based semantic search system.

RDF and OWL Storage and Query Processing based on Relational Database (관계형 데이타베이스 기반의 RDF와 OWL의 저장 및 질의처리)

  • Jeong Hoyoung;Kim Jungmin;Jung Junwon;Kim Jongnam;Im Donghyuk;Kim Hyoung-Joo
    • Journal of KIISE:Computing Practices and Letters
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    • v.11 no.5
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    • pp.451-457
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    • 2005
  • In spite of the development of computers, the present state that a lot of electronic documents are overflowing makes it more difficult for us to get appropriate information. Therefore, it's more important to focus on getting meaningful information than processing the data quickly In this context, Semantic Web enables an intelligent processing by adding semantic metadata on yow web documents. Also, as the Semantic Web grows, the knowledge resources as well as web resources are getting more and more importance. In this paper, we propose an OWL storage system aiming at an intelligent Processing by adding semantic metadata on your web documents, plus a system aiming at an OWL-QL Query Processing.

Indexing and Storage Schemes for Keyword-based Query Processing over Semantic Web Data (시맨틱 웹 데이터의 키워드 질의 처리를 위한 인덱싱 및 저장 기법)

  • Kim, Youn-Hee;Shin, Hye-Yeon;Lim, Hae-Chull;Chong, Kyun-Rak
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.5
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    • pp.93-102
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    • 2007
  • Metadata and ontology can be used to retrieve related information through the inference mure accurately and simply on the Semantic Web. RDF and RDF Schema are general languages for representing metadata and ontology. An enormous number of keywords on the Semantic Web are very important to make practical applications of the Semantic Web because most users prefer to search with keywords. In this paper, we consider a resource as a unit of query results. And we classily queries with keyword conditions into three patterns and propose indexing techniques for keyword-search considering both metadata and ontology. Our index maintains resources that contain keywords indirectly using conceptual relationships between resources as well as resources that contain keywords directly. So, if user wants to search resources that contain a certain keyword, all resources are retrieved using our keyword index. We propose a structure of table for storing RDF Schema information that is labeled using some simple methods.

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Automatic Generation of RDF Metadata for Semantic Search in Semantic Web (시맨틱 웹에서 의미 검색을 위한 RDF 메타데이타 자동 생성)

  • 강상구;양재영;양승섭;최원종;최중민
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.311-320
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    • 2002
  • 시맨틱 웹은 인간이 이해하는 것처럼 웹 문서의 의미를 컴퓨터가 처리할 수 있도록 하는데 있다. 그러나 인터넷 등 정보통신 기술의 발전으로 인해 정보량이 급증함으로써 이들 정보 자원을 효과적으로 검색하기에는 많은 어려움이 있다. 이러한 문제점을 해결하기 위해 본 논문에서는 주석 에디터를 사용하여 논문에 대한 RDF 메타데이타의 자동 생성 방법을 제안한다. 사용자가 논문을 주석 처리할 때, 문서에 대한 특징을 추출하고 온토로지 인터페이스를 사용하여 문서를 분류한다. 구현된 시스템을 통해 사용자는 추출된 메타데이타를 메타데이타 뷰를 통해 볼 수 있으며, HTML 뷰를 통해 메타데이타를 수동으로 수정이 가능하다. 이 메타데이타는 RDF Repository로 저장할 수 있으며, 주석 뷰를 통하여 RDF 메타데이타 생성을 확인할 수 있다. 이렇게 생성된 RDF 메타데이타는 웹 로봇이 내용의 의미 파악 및 카테고리 정보를 쉽게 알 수 있도록 해준다. 본 논문은 검색 엔진을 통하여 논문 검색시 전체 내용보다 RDF 메타데이타 정보만으로 효율적인 검색을 할 수 있는 방법에 초점을 둔다.

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A Tensor Space Model based Semantic Search Technique (텐서공간모델 기반 시멘틱 검색 기법)

  • Hong, Kee-Joo;Kim, Han-Joon;Chang, Jae-Young;Chun, Jong-Hoon
    • The Journal of Society for e-Business Studies
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    • v.21 no.4
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    • pp.1-14
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    • 2016
  • Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

A Study on Distribution Query Conversion Method for Real-time Integrating Retrieval based on TMDR (TMDR 기반의 실시간 통합 검색을 위한 분산질의 변환 기법에 대한 연구)

  • Hwang, Chi-Gon;Shin, Hyo-Young;Jung, Kye-Dong;Choi, Young-Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.7
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    • pp.1701-1707
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    • 2010
  • This study is intended for implementing the system environment that can help integrate and retrieve various types of data in real-time by providing semantic interoperability among distributed heterogeneous information systems. The semantic interoperability is made possible by providing a TMDR(Topicmaps Metadata Registry), a set of ontologies. TMDR, which has been made by combining MDR(MetaData Registry) and TopicMaps and storing them in the database, is able to generate distributed query and provide efficient knowledge. MDR is a metadata management technique for distributed data management. TopicMaps is an ontology representation technique that takes into consideration the hierarchy and association for accessing knowledge data. We have created TMDR, a kind of ontology, that is fit for any system and able to detect and resolve semantic conflicts on the level of data and schema. With this system we propose a query-processing technique to integrate and access heterogeneous information sources. Unlike existing retrieval methods this makes possible efficient retrieval and reasoning by providing association focusing on subjects.

Standard Terminology System Referenced by 3D Human Body Model

  • Choi, Byung-Kwan;Lim, Ji-Hye
    • Journal of information and communication convergence engineering
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    • v.17 no.2
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    • pp.91-96
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    • 2019
  • In this study, a system to increase the expressiveness of existing standard terminology using three-dimensional (3D) data is designed. We analyze the existing medical terminology system by searching the reference literature and perform an expert group focus survey. A human body image is generated using a 3D modeling tool. Then, the anatomical position of the human body is mapped to the 3D coordinates' identification (ID) and metadata. We define the term to represent the 3D human body position in a total of 12 categories, including semantic terminology entity and semantic disorder. The Blender and 3ds Max programs are used to create the 3D model from medical imaging data. The generated 3D human body model is expressed by the ID of the coordinate type (x, y, and z axes) based on the anatomical position and mapped to the semantic entity including the meaning. We propose a system of standard terminology enabling integration and utilization of the 3D human body model, coordinates (ID), and metadata. In the future, through cooperation with the Electronic Health Record system, we will contribute to clinical research to generate higher-quality big data.