The Quest for Parallel Reasoning on the Semantic Web

  • Peiqiang Li
  • Yi Zeng
  • Spyros Kotoulas
  • Jacopo Urbani
  • Ning Zhong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5820)


Traditional reasoning tools for the Semantic Web cannot cope with Web scale data. One major direction to improve performance is parallelization. This article surveys existing studies, basic ideas and mechanisms for parallel reasoning, and introduces three major parallel applications on the Semantic Web: LarKC, MaRVIN, and Reasoning-Hadoop. Furthermore, this paper lays the ground for parallelizing unified search and reasoning at Web scale.


  1. 1.
    Berners-Lee, T.: The semantic web. Scientific American 6, 1–6 (2001)Google Scholar
  2. 2.
    Fensel, D., van Harmelen, F.: Unifying reasoning and search to web scale. IEEE Internet Computing 11(2), 94–95 (2007)CrossRefGoogle Scholar
  3. 3.
    Fensel, D., van Harmelen, F., Andersson, B., Brennan, P., Cunningham, H., Valle, E., Fischer, F., Huang, Z., Kiryakov, A., Lee, T., School, L., Tresp, V., Wesner, S., Witbrock, M., Zhong, N.: Towards larkc: A platform for web-scale reasoning. In: Proceedings of the International Conference on Semantic Computing, pp. 524–529 (2008)Google Scholar
  4. 4.
    Urbani, J., Kotoulas, S., Oren, E., van Harmelen, F.: Scalable distributed reasoning using mapreduce. In: Proceedings of the International Semantic Web Conference (2009)Google Scholar
  5. 5.
    Oren, E., Kotoulas, S., Anadiotis, G., Siebes, R., Ten Teije, A., van Harmelen, F.: Marvin: distributed reasoning over large-scale semantic web data. Journal of Web Semantics (to appear)Google Scholar
  6. 6.
    Flynn, M.: Very high-speed computing systems. Proceedings of the IEEE 54(12), 1901–1909 (1966)CrossRefGoogle Scholar
  7. 7.
    Gallizo, G., Roller, S., Tenschert, A., Witbrock, M., Bishop, B., Keller, U., van Harmelen, F., Tagni, G., Oren, E.: Summary of parallelisation and control approaches and their exemplary application for selected algorithms or applications. In: LarKC Project Deliverable 5.1, pp. 1–30 (2008)Google Scholar
  8. 8.
    Wilkinson, B., Allen, M.: Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers, 2nd edn. Prentice-Hall, Englewood Cliffs (2005)Google Scholar
  9. 9.
    Robert, B.: Japan’s pipedream: The fifth generation project. System and Software September 3, 91–92 (1984)Google Scholar
  10. 10.
    Ehud, S.: Systolic programming: A paradigm of parallel processing. In: Proceedings of the international conference on Fifth Generation Computer Systems, pp. 458–470 (1984)Google Scholar
  11. 11.
    Liu, Z., You, J.: Dynamic load-balancing on a parallel inference system. In: Proceedings of the Second IEEE Symposium on Parallel and Distributed Processing, pp. 58–61 (1990)Google Scholar
  12. 12.
    Tan, X., Zhang, X., Gao, Q.: Load sharing algorithms for parallel inference machine epim–ldshbs, intldsh. Chinese journal of computers (5), 321–331 (1986)Google Scholar
  13. 13.
    Allemang, D., Hendler, J.: Semantic Web for the Working Ontologiest. Elsevier, Inc., Amsterdam (2008)Google Scholar
  14. 14.
    Brachman, R., Levesque, H.: Knowledge Representation and Reasoning. Elsevier, Inc., Amsterdam (2004)Google Scholar
  15. 15.
    Soma, S., Prasanna, V.: Parallel inferencing for owl knowledge bases. In: Proceedings of the 37th International Conference on Parallel Processing, pp. 75–82 (2008)Google Scholar
  16. 16.
    Schlicht, A., Stuckenschmidt, H.: Distributed resolution for alc. In: Proceedings of the International Workshop on Description Logic (2008)Google Scholar
  17. 17.
    Oren, E.: Goal: Making pipline scale. Technical report, LarKC 1st Early Adopters Workshop (June 2009)Google Scholar
  18. 18.
    van Nieuwpoort, R., Maassen, J., Wrzesinska, G., Hofman, R., Jacobs, C., Kielmann, T., Bal, H.: Ibis: a flexible and efficient java based grid programming environment. Concurrency and Computation: Practice and Experience 17(7-8), 1079–1107 (2005)CrossRefGoogle Scholar
  19. 19.
    Chapman, B., Jost, G., van der Pas, R., Kuck, D.: Using OpenMP: Portable Shared Memory Parallel Programming. The MIT Press, Cambridge (2007)Google Scholar
  20. 20.
    Bornemann, M., van Nieuwpoort, R., Kielmann, T.: Mpj/ibis: a flexible and efficient message passing platform for java. In: Proceedings of 12th European PVM/MPI Users’ Group Meeting, pp. 217–224 (2005)Google Scholar
  21. 21.
    Hayes, P.: Rdf semantics. In: W3C Recommendation (2004)Google Scholar
  22. 22.
    Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: Proceedings of the 6th Symposium on Operating Systems Design and Implementation, pp. 137–150 (2004)Google Scholar
  23. 23.
    Hobbs, J.: Granularity. In: Proceedings of the 9th International Joint Conference on Artificial Intelligence, pp. 432–435 (1985)Google Scholar
  24. 24.
    Yao, Y.: A unified framework of granular computing. In: Handbook of Granular Computing, pp. 401–410. Wiley, Chichester (2008)CrossRefGoogle Scholar
  25. 25.
    Zeng, Y., Wang, Y., Huang, Z., Zhong, N.: Unifying web-scale search and reasoning from the viewpoint of granularity. In: Liu, J., et al. (eds.) AMT 2009. LNCS, vol. 5820, pp. 418–429. Springer, Heidelberg (2009)Google Scholar
  26. 26.
    Serafini, L., Tamilin, A.: Drago: Distributed reasoning architecture for the semantic web. In: Proceedings of the European Semantic Web Conference, pp. 361–376 (2005)Google Scholar
  27. 27.
    Howe, A., Dreilinger, D.: Savvysearch: a meta-search engine that learns which search engines to query. AI Magazine 18(2), 19–25 (1997)Google Scholar
  28. 28.
    Chabuk, T., Seifter, M., Salasin, J., Reggia, J.: Integrating knowledge-based and case-based reasoning. Technical report, University of Maryland (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Peiqiang Li
    • 1
  • Yi Zeng
    • 1
  • Spyros Kotoulas
    • 2
  • Jacopo Urbani
    • 2
  • Ning Zhong
    • 1
    • 3
  1. 1.International WIC InstituteBeijing University of TechnologyBeijingP.R. China
  2. 2.Department of Computer ScienceVU University AmsterdamAmsterdamThe Netherlands
  3. 3.Department of Life Science and InformaticsMaebashi Institute of TechnologyMaebashiJapan

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