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Scalable Instance Retrieval for the Semantic Web by Approximation

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Web Information Systems Engineering – WISE 2005 Workshops (WISE 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3807))

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Abstract

Approximation has been identified as a potential way of reducing the complexity of logical reasoning. Here we explore approximation for speeding up instance retrieval in a Semantic Web context. For OWL ontologies, i.e., Description Logic (DL) Knowledge Bases, it is known that reasoning is a hard problem. Especially in instance retrieval when the number of instances that need to be retrieved becomes very large. We discuss two approximation methods for retrieving instances to conjunctive queries over DL T-Boxes and the results of experiments carried out with a modified version of the Instance Store System.

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References

  1. Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F.: The Description Logic Handbook - Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)

    MATH  Google Scholar 

  2. Groot, P., Stuckenschmidt, H., Wache, H.: Approximating Description Logic Classification for Semantic Web Reasoning. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005, vol. 3532, pp. 318–332. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Haarslev, V., Möller, R.: RACE system description. In: Proceedings of the 1999 DL Workshop, CEUR Electronic Workshop Proceedings, pp. 130–132 (1999)

    Google Scholar 

  4. Haarslev, V., Möller, R.: High performance reasoning with very large knowledge bases: A practical case study. In: IJCAI 2001, pp. 161–168 (2001)

    Google Scholar 

  5. Haarslev, V., Möller, R.: RACER system description. In: Goré, R.P., Leitsch, A., Nipkow, T. (eds.) IJCAR 2001. LNCS, vol. 2083, pp. 701–705. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  6. Horrocks, I.: The FACT system. In: de Swart, H. (ed.) TABLEAUX 1998. LNCS, vol. 1397, pp. 307–312. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  7. Horrocks, I.: Using an Expressive Description Logic: FaCT or Fiction? In: KR 1998, pp. 636–647. Morgan Kaufmann, San Francisco (1998)

    Google Scholar 

  8. Horrocks, I., Li, L., Turi, D., Bechhofer, S.: The Instance Store: DL Reasoning with Large Numbers of Individuals. In: Proc. of the 2004 DL Workshop (2004)

    Google Scholar 

  9. Horrocks, I., Tessaris, S.: A Conjunctive Query Language for Description Logic Aboxes. In: AAAI, pp. 399–404 (2000)

    Google Scholar 

  10. Schaerf, M., Cadoli, M.: Tractable reasoning via approximation. Artificial Intelligence 74, 249–310 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  11. Stuckenschmidt, H., van Harmelen, F.: Approximating terminological queries. In: Andreasen, T., Motro, A., Christiansen, H., Larsen, H.L. (eds.) FQAS 2002. LNCS, vol. 2522, pp. 329–343. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. Vrije Universiteit Amsterdam, de Boelelaan 1081a, 1081HV, Amsterdam, The Netherlands

    Holger Wache & Heiner Stuckenschmidt

  2. Radboud University Nijmegen, Toernooiveld 1, 6500GL, Nijmegen, The Netherlands

    Perry Groot

Authors
  1. Holger Wache
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  2. Perry Groot
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  3. Heiner Stuckenschmidt
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Editor information

Editors and Affiliations

  1. BBN Technologies, 48103, Ann Arbor, USA

    Mike Dean

  2.  ,  

    Yuanbo Guo

  3. Dept. of Computer Education, Seoul National University of Education, Seoul, Korea

    Woochun Jun

  4. School of Engineering and Advanced Technology, Massey University, New Zealand

    Roland Kaschek

  5. Caulfield School of Information Technology, Monash University, VIC 3145, Caulfield East, Australia

    Shonali Krishnaswamy

  6. Department of Computer Science and Engineering, Lehigh University, 19 Memorial Dr., PA 18015, West, Bethlehem, U.S.A.

    Zhengxiang Pan

  7. School of Computer Science and Engineering, University of New South Wales, NSW 2052, Sydney, Australia

    Quan Z. Sheng

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© 2005 Springer-Verlag Berlin Heidelberg

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Wache, H., Groot, P., Stuckenschmidt, H. (2005). Scalable Instance Retrieval for the Semantic Web by Approximation. In: Dean, M., et al. Web Information Systems Engineering – WISE 2005 Workshops. WISE 2005. Lecture Notes in Computer Science, vol 3807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581116_26

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  • DOI: https://doi.org/10.1007/11581116_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30018-2

  • Online ISBN: 978-3-540-32287-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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