Adapting the Pyramid Technique for Indexing Ontological Data

  • Övünç Öztürk
  • Tuğba Özacar
  • Murat Osman Ünalır
  • Ata Önal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4263)


This paper describes the implementation of an indexing mechanism on a Rete-based reasoner working with ontological data in order to optimize memory consumption of the reasoner. This newly introduced indexing mechanism is known as the Pyramid Technique [1]. Our work organizes three dimensional ontological data in a way that works efficiently with this indexing mechanism and it constructs a subset of the querying scheme of the Pyramid Technique that supports querying ontological data. This work also implements an optimization on the Pyramid Technique. Finally, it discusses the performance analysis of the reasoner in terms of time and memory consumptions.


Range Query Point Query Inference Engine Memory Consumption Query Answer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Berchtold, S., Böhm, C., Kriegel, H.P.: The pyramid-technique: Towards breaking the curse of dimensionality. In: Haas, L.M., Tiwary, A. (eds.) SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, Seattle, Washington, USA, June 2-4, 1998, pp. 142–153. ACM Press, New York (1998)CrossRefGoogle Scholar
  2. 2.
    Guo, Y., Pan, Z., Heflin, J.: An evaluation of knowledge base systems for large owl datasets. In: International Semantic Web Conference, pp. 274–288 (2004)Google Scholar
  3. 3.
    Forgy, C.: Rete: A fast algorithm for the many patterns/many objects match problem. Artif. Intell. 19, 17–37 (1982)CrossRefGoogle Scholar
  4. 4.
    Doorenbos, R.B.: Production matching for large learning systems. Technical report, Pittsburgh, PA, USA (2001)Google Scholar
  5. 5.
    Franconi, E., Tessaris, S.: Rules and Queries with Ontologies: A Unified Logical Framework. In: Ohlbach, H.J., Schaffert, S. (eds.) PPSWR 2004. LNCS, vol. 3208, pp. 50–60. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Ishida, T.: Optimizing rules in production system programs. In: National Conference on Artificial Intelligence, pp. 699–704 (1988)Google Scholar
  7. 7.
    Ünalir, M., Özacar, T., Öztürk, Ö.: Reordering query and rule patterns for query answering in a rete-based inference engine. In: WISE Workshops, pp. 255–265 (2005)Google Scholar
  8. 8.
    Jagadish, H.V., Koudas, N., Srivastava, D.: On effective multi-dimensional indexing for strings. In: SIGMOD 2000: Proceedings of the 2000 ACM SIGMOD international conference on Management of data, pp. 403–414. ACM Press, New York (2000)CrossRefGoogle Scholar
  9. 9.
    Zhang, R., Ooi, B.C., Tan, K.L.: Making the pyramid technique robust to query types and workloads. In: ICDE, pp. 313–324 (2004)Google Scholar
  10. 10.
    Kopena, J., Regli, W.C.: Damljesskb: A tool for reasoning with the semantic web. In: International Semantic Web Conference, pp. 628–643 (2003)Google Scholar
  11. 11.
    Carroll, J.J., Roo, J.D.: Owl web ontology language test cases (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Övünç Öztürk
    • 1
  • Tuğba Özacar
    • 1
  • Murat Osman Ünalır
    • 1
  • Ata Önal
    • 1
  1. 1.Department of Computer EngineeringEge UniversityBornovaTurkey

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