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A Heuristics Framework for Semantic Subscription Processing

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5554)

Abstract

The increasing adoption of semantic web technology in application scenarios with frequently changing data has imposed new requirements on the underlying tools. Reasoning algorithms need to be optimized for the processing of dynamic knowledge bases and semantic frameworks have to provide novel mechanisms for detecting changes of knowledge. Today, the latter is mostly realized by implementing simple polling mechanisms. However, this implies client-side post-processing of the received results, causes high response times and limits the overall throughput of the system. In this paper, we present a heuristics framework for realizing a subscription mechanism for dynamic knowledge bases. By analyzing similarities between published information and resulting notifications, heuristics can be employed to “guess” subsequent notifications. As testing the correctness of guessed notifications can be implemented efficiently, notifications can be delivered to the subscribers in an earlier processing phase and the system throughput can be increased. We experimentally evaluate our approach based on a concrete application scenario.

Keywords

Semantic subscription processing heuristics framework continuous queries similarity heuristics incremental result set updates 
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References

  1. 1.
    Nixon, L.J.B., Teymourian, K., Krummenacher, R., Moritsch, H., Momtchev, V., Ghioni, A., Schütz, A.: Semantic Clustering and Self-Organisation in Triple Space, TripCom Research Deliverable (2008), http://www.tripcom.org/docs/del/D2.4.pdf
  2. 2.
    Catarci, T., Lenzerini, M.: Representing and Using Interschema Knowledge in Cooperative Information Systems. Journal of Intelligent and Cooperative Information Systems 2(4), 375–398 (1993)CrossRefGoogle Scholar
  3. 3.
    Murth, M., Kühn, e.: A Semantic Event Notification Service for Knowledge-Driven Coordination. In: Proc. of 1st Int’l. workshop on emergent semantics and cooperation in open systems (ESTEEM), cooperation with the 2nd Int’l. Conf. on Distributed Event-Based Systems (DEBS 2008), Rome, Italy, July 1 (2008)Google Scholar
  4. 4.
    Petrovic, M., Liu, H., Jacobsen, H.: G-ToPSS: Fast Filtering of Graph-based Metadata. In: Proceedings of the 14th International Conference on World Wide Web (WWW 2005). ACM Press, New York (2005)Google Scholar
  5. 5.
    Wang, J., Jin, B., Li, J.: An ontology-based publish/Subscribe system. In: Jacobsen, H.-A. (ed.) Middleware 2004. LNCS, vol. 3231, pp. 232–253. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Murth, M., Kühn, e.: Knowledge-based Coordination with a Reliable Semantic Subscription Mechanism. In: Proc. of 24th ACM Symposium of Applied Computing (SAC 2009) – Special Track on Coordination Models, Languages and Applications. ACM Press, Honolulu (2009)Google Scholar
  7. 7.
    Nixon, L.J.B., Simperl, E., Krummenacher, R., Martin-Recuerda, F.: Tuplespace-based Computing for the Semantic Web: A Survey of the State-of-the-Art. The Knowledge Engineering Review 23(2) (2008)Google Scholar
  8. 8.
    Halaschek-Wiener, C., Parsia, B., Sirin, E.: Description logic reasoning with syntactic updates. In: Meersman, R., Tari, Z. (eds.) OTM 2006. LNCS, vol. 4275, pp. 722–737. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F.: The Description Logic Handbook: Theory, Implementation, Applications. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  10. 10.
    Khushraj, D., Lassila, O., Finin, T.W.: sTuples: Semantic Tuple Spaces. In: 1st Ann. Int’l. Conf. on Mobile and Ubiquitous Systems (2004)Google Scholar
  11. 11.
    Fensel, D., Krummenacher, R., Shafiq, O., Kühn, e., Riemer, J., Ding, Y., Draxler, B.: TSC - Triple Space Computing, In Special issue on ICT research in Austria. Journal of Electronics & Information Technology (e&i Elektrotechnik & Informationstechnik) (January-February 2007)Google Scholar
  12. 12.
    Nixon, L.J.B., Paslaru Bontas Simperl, E., Antonenko, O., Tolksdorf, R.: Towards Semantic Tuplespace Computing: The Semantic Web Spaces System. In: 22nd Ann. ACM Symposium on Applied Computing (2007)Google Scholar
  13. 13.
    Simperl, E., Krummenacher, R., Nixon, L.: A Coordination Model for Triplespace Computing. In: Murphy, A.L., Vitek, J. (eds.) COORDINATION 2007. LNCS, vol. 4467, pp. 1–18. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. 14.
    Gelernter, D.: Generative Communication in Linda. ACM Transactions in Programming Languages and Systems (TOPLAS) 7(1), 80–112 (1985)CrossRefzbMATHGoogle Scholar
  15. 15.
    Cerzza, D., Della Valle, E., Foxvog, D., Krummenacher, R., Murth, M.: Towards European Patient Summaries based on Triple Space Computing. In: Proc. of 1st European Conf. on eHealth, Fribourg, Switzerland, October 12-13 (2006)Google Scholar
  16. 16.
    Jena. Jena – A Semantic Web Framework for Java, http://jena.sourceforge.net/ (last accessed: September 2007)
  17. 17.
    Broekstra, J., Kampman, A., van Harmelen, F.: Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 54–68. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  18. 18.
    ARQ – A SPARQL Processor for Jena, http://jena.sourceforge.net/ARQ/
  19. 19.
    Kaon2. Ontology management for the semantic web, http://kaon2.semanticweb.org/
  20. 20.
    Cai, M., Frank, M.: RDFPeers: A Scalable Distributed RDF Repository Based on a Structured Peer-to-Peer Network. In: 13th Int’l. Conference on World Wide Web (2004)Google Scholar
  21. 21.
    Liarou, E., Idreos, S., Koubarakis, M.: Continuous RDF Query Processing over DHTs. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 324–339. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  22. 22.
    Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF. W3C Recommendation (2008), http://www.w3.org/TR/rdf-sparql-query/
  23. 23.
    Luckham, D.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley, Reading (2002)Google Scholar
  24. 24.
    Guo, Y., Pan, Z., Heflin, J.: LUBM: A Benchmark for OWL Knowledge Base Systems. Journal of Web Semantics 3(2), 158–182 (2005)CrossRefGoogle Scholar
  25. 25.
  26. 26.
    Manola, F., Miller, E.: RDF Primer W3C-Recommend (2004), http://www.w3.org/TR/rdf-primer/
  27. 27.
    McGuinness, D.L., van Harmelen, F.: OWL Web Ontology Language, W3C Recommendation (2004), http://www.w3.org/TR/owl-features/

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Institute of Computer Languages, Space Based Computing GroupVienna University of TechnologyViennaAustria

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