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Linkage Expansion in Linked Open Data Cloud using Link Policy

연결정책을 이용한 개방형 연결 데이터 클라우드에서의 연결성 확충

  • 김광민 (서경대학교 대학원 전자컴퓨터공학과) ;
  • 손용락 (서경대학교 컴퓨터공학과)
  • Received : 2017.05.11
  • Accepted : 2017.09.13
  • Published : 2017.10.15

Abstract

This paper suggests a method to expand linkages in a Linked Open Data(LOD) cloud that is a practical consequence of a semantic web. LOD cloud, contrary to the first expectation, has not been used actively because of the lack of linkages. Current method for establishing links by applying to explicit links and attaching the links to LODs have restrictions on reflecting target LODs' changes in a timely manner and maintaining them periodically. Instead of attaching them, this paper suggests that each LOD should prepare a link policy and publish it together with the LOD. The link policy specifies target LODs, predicate pairs, and similarity degrees to decide on the establishment of links. We have implemented a system that performs in-depth searching through LODs using their link policies. We have published APIs of the system to Github. Results of the experiment on the in-depth searching system with similarity degrees of 1.0 ~ 0.8 and depth level of 4 provides searching results that include 91% ~ 98% of the trustworthy links and about 170% of triples expanded.

본 논문은 시멘틱 웹의 실제적인 구현 결과인 개방형 연결 데이터(Linked Open Data(LOD)) 클라우드에서의 연결성을 확충하는 방안을 제시하였다. 현재의 LOD 클라우드는 최초 기대와는 달리 LOD들간의 연결성 부족으로 인하여 활발한 활용을 이끌어 내지 못하고 있다. 를 적용한 명시적연결들을 LOD에 직접 첨부하여 공개하는 현재의 연결방식은 연결대상 LOD들의 변경상황을 실시간으로 검색결과에 반영하지 못하며 별도의 작업을 통하여 이러한 명시적연결들을 생성하고 주기적으로 갱신하여야 한다는 제약을 가진다. 이에 본 논문은 명시적연결들을 첨부하는 대신 LOD마다 연결정책을 마련하고 이를 LOD와 함께 공개하는 방안을 제안하였다. 연결정책에는 타겟LOD들을 선정하고 연결판단에 필요한 술어 쌍들과 유사도를 명세하도록 하였다. 이러한 연결정책에 기반하여 여러 LOD들에 거쳐 진행하는 심층검색 기능을 API로 구현하고 이를 Github를 통하여 공개하였다. 구현한 심층검색을 유사도 1.0~0.8, 깊이 4까지에서 실험한 결과 신뢰적인 연결들을 91%~98% 수준으로 포함하고 170% 정도 규모의 적정한 확장성을 제공하는 것으로 평가되었다.

Acknowledgement

Supported by : 서경대학교

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