Abstract
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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Berners-Lee, T.: The semantic web. Scientific American 6, 1–6 (2001)
Fensel, D., van Harmelen, F.: Unifying reasoning and search to web scale. IEEE Internet Computing 11(2), 94–95 (2007)
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)
Urbani, J., Kotoulas, S., Oren, E., van Harmelen, F.: Scalable distributed reasoning using mapreduce. In: Proceedings of the International Semantic Web Conference (2009)
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)
Flynn, M.: Very high-speed computing systems. Proceedings of the IEEE 54(12), 1901–1909 (1966)
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)
Wilkinson, B., Allen, M.: Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers, 2nd edn. Prentice-Hall, Englewood Cliffs (2005)
Robert, B.: Japan’s pipedream: The fifth generation project. System and Software September 3, 91–92 (1984)
Ehud, S.: Systolic programming: A paradigm of parallel processing. In: Proceedings of the international conference on Fifth Generation Computer Systems, pp. 458–470 (1984)
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)
Tan, X., Zhang, X., Gao, Q.: Load sharing algorithms for parallel inference machine epim–ldshbs, intldsh. Chinese journal of computers (5), 321–331 (1986)
Allemang, D., Hendler, J.: Semantic Web for the Working Ontologiest. Elsevier, Inc., Amsterdam (2008)
Brachman, R., Levesque, H.: Knowledge Representation and Reasoning. Elsevier, Inc., Amsterdam (2004)
Soma, S., Prasanna, V.: Parallel inferencing for owl knowledge bases. In: Proceedings of the 37th International Conference on Parallel Processing, pp. 75–82 (2008)
Schlicht, A., Stuckenschmidt, H.: Distributed resolution for alc. In: Proceedings of the International Workshop on Description Logic (2008)
Oren, E.: Goal: Making pipline scale. Technical report, LarKC 1st Early Adopters Workshop (June 2009)
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)
Chapman, B., Jost, G., van der Pas, R., Kuck, D.: Using OpenMP: Portable Shared Memory Parallel Programming. The MIT Press, Cambridge (2007)
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)
Hayes, P.: Rdf semantics. In: W3C Recommendation (2004)
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)
Hobbs, J.: Granularity. In: Proceedings of the 9th International Joint Conference on Artificial Intelligence, pp. 432–435 (1985)
Yao, Y.: A unified framework of granular computing. In: Handbook of Granular Computing, pp. 401–410. Wiley, Chichester (2008)
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)
Serafini, L., Tamilin, A.: Drago: Distributed reasoning architecture for the semantic web. In: Proceedings of the European Semantic Web Conference, pp. 361–376 (2005)
Howe, A., Dreilinger, D.: Savvysearch: a meta-search engine that learns which search engines to query. AI Magazine 18(2), 19–25 (1997)
Chabuk, T., Seifter, M., Salasin, J., Reggia, J.: Integrating knowledge-based and case-based reasoning. Technical report, University of Maryland (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, P., Zeng, Y., Kotoulas, S., Urbani, J., Zhong, N. (2009). The Quest for Parallel Reasoning on the Semantic Web. In: Liu, J., Wu, J., Yao, Y., Nishida, T. (eds) Active Media Technology. AMT 2009. Lecture Notes in Computer Science, vol 5820. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04875-3_45
Download citation
DOI: https://doi.org/10.1007/978-3-642-04875-3_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04874-6
Online ISBN: 978-3-642-04875-3
eBook Packages: Computer ScienceComputer Science (R0)