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의미적 관계를 이용한 OWL 데이터의 키워드 질의 처리 기법

A Keyword Query Processing Technique of OWL Data using Semantic Relationships

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참고문헌

키워드

초록

In this paper, we propose a keyword query processing technique based on semantic relationships for OWL data. The proposed keyword query processing technique can improve user’s search satisfaction by performing two types of associative search. The first associative search uses information inferred by the relationships between classes or properties during keyword query processing. And it supports to search all information resources that are either directly or indirectly related with query keywords by semantic relationships between information resources. The second associative search returns not only information resources related with query keywords but also values of properties of them. We design a storage schema and index structures to support the proposed technique. And we propose evaluation functions to rank retrieved information resources according to three criteria. Finally, we evaluate the validity and accuracy of the proposed technique through experiments. The proposed technique can be utilized in a variety of fields, such as paper retrieval and multimedia retrieval.

Abstract

In this paper, we propose a keyword query processing technique based on semantic relationships for OWL data. The proposed keyword query processing technique can improve user’s search satisfaction by performing two types of associative search. The first associative search uses information inferred by the relationships between classes or properties during keyword query processing. And it supports to search all information resources that are either directly or indirectly related with query keywords by semantic relationships between information resources. The second associative search returns not only information resources related with query keywords but also values of properties of them. We design a storage schema and index structures to support the proposed technique. And we propose evaluation functions to rank retrieved information resources according to three criteria. Finally, we evaluate the validity and accuracy of the proposed technique through experiments. The proposed technique can be utilized in a variety of fields, such as paper retrieval and multimedia retrieval.

참고문헌 (8)

  1. 김성림, "A Study on Recommendation Method Based on Web 3.0", (사)디지털산업정보학회 논문지, 8(4), pp.43~51 (2012), (사)디지털산업정보학회
  2. "OWL 2 Web Ontology Language Primer"[URL]
  3. 김연희, "시맨틱 웹 문서에 대한 키워드 검색 및 랭킹 기법", 통신위성우주산업연구회논문지, 7(3), pp.86~93 (2012), 사단법인 통신위성우주산업연구회
  4. 김진하, "RDF 데이타에 대한 효율적인 키워드 검색 기법", 정보과학회논문지 : 데이타베이스, 35(6), pp.495~504 (2008), 한국정보과학회
  5. Jihyun Lee, "An Effective Semantic Search Technique using Ontology", Proceeding of WWW, pp.1057~1058 (2009)
  6. 김학수, "RDF", S 및 OWL 문서에 대한 키워드 검색 알고리즘, 2009, pp.16(1), 321~324
  7. 박창섭, "의미적 연관성을 이용한 멀티미디어 정보 검색", 인터넷정보학회논문지, 8(5), pp.67~79 (2007), 한국인터넷정보학회
  8. 김병준, "시맨틱 웹 데이터에서 키워드 검색을 위한 구조 질의 랭킹 기법", 정보과학회논문지 : 데이타베이스, 39(2), pp.138~146 (2012), 한국정보과학회[DOI]

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