The Journal of Society for e-Business Studies (한국전자거래학회지)

Society for e-Business Studies (한국전자거래학회)
권호 표지
DOI QR코드

DOI QR Code

Index for Efficient Ontology Retrieval and Inference

효율적인 온톨로지 검색과 추론을 위한 인덱스

  • Received : 2013.01.21
  • Accepted : 2013.05.14
  • Published : 2013.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.

근래에 들어와서 각광받고 있는 시맨틱 웹과 관련기술의 부상으로 온톨로지에 대한 관심이 증대되었으며, 그중에서도 고난이도의 추론을 요구하는 의미기반 시맨틱 검색을 위해서 온톨로지를 효율적으로 저장하고 검색하는 다양한 기법들이 활발히 연구되어왔다. W3C에서의 표준권고안은 RDFS, OWL을 활용하도록 하고 있다. 하지만 메모리 기반으로 구현되어 있는 에디터나 추론엔진들, 온톨로지의 원형을 그대로 유지하여 저장하는 트리플 저장소를 이용하여 대용량 온톨로지를 처리하기에는 성능상의 한계가 있다. 따라서 이를 해결하기 위해 관계형 데이터베이스 엔진을 이용하여, 온톨로지를 저장하고 효율적으로 활용하기 위한 다양한 방식의 추론엔진과 질의처리 알고리즘들이 제안되었으나, 온톨로지 프로퍼티의 다섯 가지 핵심특성에 따른 추론 결과를 완전하게 획득하지는 못하고 있는 실정이다. 본 논문에서는 하이퍼 큐브 인덱스(Hyper Cube Index)를 제안함으로서 관계형 데이터베이스에 저장한 온톨로지를 효율적으로 검색할 수 있는 환경을 제공하는 것은 물론, 온톨로지 프로퍼티의 핵심특성을 빠짐없이 투영하여 숨겨진 추론 결과를 획득할 수 있는 방안을 제시한다.

Keywords

References

  1. Antoshenkov, G., "Byte-aligned bitmap compression," In Proc. DCC'95, p. 476, 1995.
  2. Berners-Lee, T., Hendler, J., and Lassila, O., "The Semantic Web," Scientific America, 2001.
  3. Brickley, D. and Guha, R. V., "Resource Description Framework(RDF) Schema Specication 1.0," Candidate recommendation, World Wide Web Consortium, March 2000.
  4. Broekstra, J., Kampman, A., and van Harmelen, F., "Sesame : A generic Architecture for StOR and Querying RDF and RDF Schema," In proc. of International Semantic Web Conference, Sardinia, Italia, pp. 54-68, 2002.
  5. Bull, J., Westhead, M., Kambites, M., and Obdrzalek, J., "Towards OpenMP for Java," In European Workshop on Open MP, 2000.
  6. CNN, "Issue of Fortune," Vol. 163, No. 5, 2011.
  7. Extensible Markup Language(XML), http://www.w3.org/XML/.
  8. Grigoris Antoniou and Frank van Harmelen, "A Semantic Web Primer" 2nd Edition, The MIT Press, 2008.
  9. Jena, http://jena.apache.org/.
  10. Lassila, O. and Swick, R. R., "Resource Description Framework(RDF) : Model and Syntax Specication.," Recommendation, World Wide Web Consortium, Feb. 1999.
  11. Lee, J. and Goodwin, R., "Ontology Management for Large-Scale E-Commerce Applications," Electronic Commerce Research and Applications, Elsevier, pp. 7-15, Sept. 2005.
  12. Lemire, D., "Enhanced Word-Aligned Hybrid(EWAH)," http://code.google.com/p/javaewah/.
  13. Lemire, D., Kaser, O., and Aouiche, K., "Sorting improves word-aligned bitmap indexes," Data and Knowledge Engineering, pp. 3-28, 2010.
  14. Lemire, D., "When is a bitmap faster than an integer list?," http://lemire.me/blog/archives/2012/10/23/when-is-a-bitmap-faster-than-an-integer-list/.
  15. Lin, J., Lee, J., and Chung, C., "An Efficient Reasoning Method for OWL Properties using Relational Databases," Journal of Korean Information Service System, Vol. 29 No. 1, pp. 92-103, 2010.
  16. McBirds, B., "Jena : A semantic web toolkit," Institute of Electrical and Electronics Engineers Internet Computing, Vol. 6, No. 6, pp. 55-59, Nov. 2002.
  17. Open MP(Open Multi-Processing), http://www.openmp.org/.
  18. Oracle Semantic Technologies, http://www.oracle.com/technetwork/database/options/semantic-tech/index.html.
  19. Pan, Z. and Heflin, J., "DLDB : Extending Relational Databases to Support Semantic Web Queries," In Proc. Practical and Scalable Semantic Systems, Sanibel Island, Florida, USA, pp. 109-113, 2003.
  20. Park, S. U., "Development of a Semantic Web Portal for Industry Knowledge Sharing," The Journal of Society for e-Business Studies, Vol. 14, No. 4, pp. 195-214, 2009.
  21. Run-Length Encoding(RLE), http://en.wikipedia.org/wiki/Run-length_encoding.
  22. Semantic Web, http://semanticweb.org.
  23. Smith, M., Welty, C., and McGuinness, D., "OWL Web Ontology Language Guide," http://www.w3.org/TR/2004/REC-owl-features-20040210/#s3.3.
  24. The Apache Software Foundation, "Apache Hadoop," http://hadoop.apache.org/.
  25. Thomas, R. Gruber, "A translation approach to porTable ontologies," Knowledge Acquisition, Vol. 5, No. 2, pp. 199-220, 1993. https://doi.org/10.1006/knac.1993.1008
  26. Volz, R., Oberle, D., Staab, S., and Motik, B., "KAON SERVER : A Semantic Web Management System," In proc. of the Atlantic Web Intelligent Conference, Hungry, Budapest, p. 29, 2003.
  27. World Wide Web Consortium (W3C), http://www.w3.org/.
  28. Wu, K., Otoo, E. J., and Shoshani, A., "Optimizing bitmap indices with efficient compression," ACM Transactions on Database Systems, pp. 1-38, 2006.
  29. Wu, Z., Eadon, G., Das, S., Chong, E. I., Kolovski, V., Annamalai, M., and Srinivasan, J., "Implementing an inference engine for RDFS/OWL constructs and user-define d rules in Oracle," InProc.ICDE-2008, pp. 1239-1248, 2008.
  30. Yoo, D. H. and Suh, Y. M., "An Ontology-based Hotel Search System Using Semantic Web Technologies," The Journal of Society for e-Business Studies, Vol. 13, No. 4, pp. 71-92, 2008.
  31. Yuanbo, Guo, Zhengxiang, Pan, and Jeff, Heflin, "LUBM : A Benchmark for OWL Knowledge Base Systems," In Proc. of International Semantic Web Conference, Hiroshima, Japan, 2004.

Cited by

  1. Knowledge Map Service based on Ontology of Nation R&D Information vol.14, pp.3, 2016, https://doi.org/10.14400/JDC.2016.14.3.251