• Title/Summary/Keyword: 링크드 데이터 클라우드

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A Study on National Linking System Implementation based on Linked Data for Public Data (공공데이터 활용을 위한 링크드 데이터 국가 연계체계 구축에 관한 연구)

  • Yoon, So-Young
    • Journal of the Korean Society for information Management
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    • v.30 no.1
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    • pp.259-284
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    • 2013
  • Public information has been collected in various fields with huge costs in order to serve public purposes such as public agencies' policy-making. However, the collected public information has been overlooked as silos. In korea, many attempts have been made to open the public information to the public only to result in limited extent, where OpenAPI data is being presented by some agencies. Recently, at the national level, the LOD(Linking Open Data) project has built the national DB, initiating the ground on which the linked data will be based for their active availability. This study has outlined overall problems in earlier projects which have built up national linking systems based on linked data for public data use. A possible solution has been proposed with a real experience of having set up an existing national DB of Korean public agencies.

A study of Reference Model of Smart Library based on Linked Open Data (링크드오픈데이터 기반 스마트 라이브러리의 참조모델에 관한 연구)

  • Moon, Hee-kyung;Han, Sung-kook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.9
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    • pp.1666-1672
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    • 2016
  • In recent years, smart technology has been applied to various information system fields. Especially, traditional library service area is changing to Smart-Library from Digital-Library. In this environment are need to library service software platform for supporting variety content, library services, users and smart-devices. Due to this, existing library service has a limitation that inhibits semantic interoperability between different heterogeneous library systems. In this paper, we propose Linked-Open-Data based smart library as an archetype of future-library system that provide a variety content and system interaction and integration of services. It is an innovative system of the cutting-edge information intensive. Therefore, we designed system environments according to various integration requirements for smart library based on Linked-Open-Data. And, we describe the functional requirements of smart-library systems by considering the users' demands and the eco-systems of information technology. In addition, we show the reference framework, which can accommodate the functional requirements and provide smart knowledge service to user through a variety of smart-devices.

DBpedia Web Search Application using Google Cloud Natural Language API (구글 클라우드 자연어 API를 이용한 DBpedia 웹 검색 애플리케이션)

  • Lee, Suhyoung;Kim, Taeyoung;Park, Sunjae;Lee, Yongju
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.509-511
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    • 2018
  • 본 논문은 링크드 오픈 데이터(Linked Open Data)의 일종인 DBpedia 개체를 자연어 기반으로 검색하는 애플리케이션 개발에 관한 논문이다. Google Cloud Natural Language API를 이용하여 자연어 입력을 분석하고, 이를 바탕으로 RDF(Resource Description Framework) 검색 언어인 스파클(Sparql) 질의 문장을 작성하여 결과를 웹 형식으로 반환해준다. 이를 통해 비문가도 손쉽게 링크드 오픈 데이터에 접근할 수 있는 기회를 제공하며 다양한 응용 가능성을 가진다.

Linked Data Indexing System for Big Data Processing on the Cloud System (빅데이터 활용을 위한 클라우드 기반의 링크드 데이터 인덱싱 시스템)

  • Lee, Mina;Jung, Jinuk;Kim, Eung-hee;Kim, Hong-gee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.1596-1598
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    • 2013
  • 2000년대 초반 등장한 시맨틱 웹 기술은 최근 재조명을 받고 있다. 이는 초기에 구축된 시맨틱 데이터와 최근에 구축하는 시맨틱 데이터의 양적 비교를 통해서도 알 수 있다. 그러나 기존의 시맨틱웹 기술은 대용량 데이터를 처리하는데 어려움이 많아, 이를 처리하기 위한 기술이 중요한 문제로 대두되고 있다. 본 논문에서는 앞에서 말한 바와 같이, 기존 RDF Repository의 대안으로, 다양한 데이터 베이스를 복합적으로 사용하였다. RDF 데이터를 효율적으로 처리하기 위해, NoSQL DB와 메모리 기반 관계형 DB를 활용하여 시스템을 구성하였다. 또한, 사용자가 이에 대한 별도의 지식 없이 기존의 SPARQL 질의를 그대로 사용하여, 원하는 결과를 얻을 수 있는 시스템을 제안한다.

A Trustworthiness Improving Link Evaluation Technique for LOD considering the Syntactic Properties of RDFS, OWL, and OWL2 (RDFS, OWL, OWL2의 문법특성을 고려한 신뢰향상적 LOD 연결성 평가 기법)

  • Park, Jaeyeong;Sohn, Yonglak
    • Journal of KIISE:Databases
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    • v.41 no.4
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    • pp.226-241
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    • 2014
  • LOD(Linked Open Data) is composed of RDF triples which are based on ontologies. They are identified, linked, and accessed under the principles of linked data. Publications of LOD data sets lead to the extension of LOD cloud and ultimately progress to the web of data. However, if ontologically the same things in different LOD data sets are identified by different URIs, it is difficult to figure out their sameness and to provide trustworthy links among them. To solve this problem, we suggest a Trustworthiness Improving Link Evaluation, TILE for short, technique. TILE evaluates links in 4 steps. Step 1 is to consider the inference property of syntactic elements in LOD data set and then generate RDF triples which have existed implicitly. In Step 2, TILE appoints predicates, compares their objects in triples, and then evaluates links between the subjects in the triples. In Step 3, TILE evaluates the predicates' syntactic property at the standpoints of subject description and vocabulary definition and compensates the evaluation results of Step 2. The syntactic elements considered by TILE contain RDFS, OWL, OWL2 which are recommended by W3C. Finally, TILE makes the publisher of LOD data set review the evaluation results and then decide whether to re-evaluate or finalize the links. This leads the publishers' responsibility to be reflected in the trustworthiness of links among the data published.

Big Data based Tourist Attractions Recommendation - Focus on Korean Tourism Organization Linked Open Data - (빅데이터 기반 관광지 추천 시스템 구현 - 한국관광공사 LOD를 중심으로 -)

  • Ahn, Jinhyun;Kim, Eung-Hee;Kim, Hong-Gee
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.129-148
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    • 2017
  • Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

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