Advertisement

Distributed Parameter Learning for Probabilistic Ontologies

  • Giuseppe Cota
  • Riccardo Zese
  • Elena Bellodi
  • Fabrizio Riguzzi
  • Evelina Lamma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9575)

Abstract

Representing uncertainty in Description Logics has recently received an increasing attention because of its potential to model real world domains. EDGE, for “Em over bDds for description loGics paramEter learning”, is an algorithm for learning the parameters of probabilistic ontologies from data. However, the computational cost of this algorithm is significant since it may take hours to complete an execution. In this paper we present \(\mathrm {EDGE}^{\mathrm {MR}}\), a distributed version of EDGE that exploits the MapReduce strategy by means of the Message Passing Interface. Experiments on various domains show that \(\mathrm {EDGE}^{\mathrm {MR}}\) significantly reduces EDGE running time.

Keywords

Probabilistic description logics Parameter learning MapReduce Message Passing Interface 

References

  1. 1.
    Ahmadi, B., Kersting, K., Mladenov, M., Natarajan, S.: Exploiting symmetries for scaling loopy belief propagation and relational training. Mach. Learn. 92(1), 91–132 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, New York (2003)zbMATHGoogle Scholar
  3. 3.
    Bellodi, E., Lamma, E., Riguzzi, F., Albani, S.: A distribution semantics for probabilistic ontologies. In: Proceedings of the 7th International Workshop on Uncertainty Reasoning for the Semantic Web. CEUR Workshop Proceedings, vol. 778, pp. 75–86. Sun SITE Central Europe (2011)Google Scholar
  4. 4.
    Bellodi, E., Riguzzi, F.: Expectation Maximization over Binary DecisionDiagrams for probabilistic logic programs. Intell. Data Anal. 17(2), 343–363 (2013)Google Scholar
  5. 5.
    Cota, G., Zese, R., Bellodi, E., Lamma, E., Riguzzi, F.: Learning probabilistic ontologies with distributed parameter learning. In: Bellodi, E., Bonfietti, A. (eds.) Proceedings of the Doctoral Consortium (DC) co-located with the 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015). CEUR Workshop Proceedings, vol. 1485, pp. 7–12. Sun SITE Central Europe, Aachen (2015)Google Scholar
  6. 6.
    Cota, G., Zese, R., Bellodi, E., Lamma, E., Riguzzi, F.: Structure learning with distributed parameter learning for probabilistic ontologies. In: Hollmen, J., Papapetrou, P. (eds.) Doctoral Consortium of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2015), pp. 75–84 (2015). http://urn.fi/URN:ISBN:978-952-60-6443-7
  7. 7.
    De Raedt, L., Kimmig, A., Toivonen, H.: ProbLog: A probabilistic Prolog and its application in link discovery. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, Hyderabad, India (IJCAI-05). vol. 7, pp. 2462–2467. AAAI Press (2007)Google Scholar
  8. 8.
    Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)CrossRefGoogle Scholar
  9. 9.
    He, Q., Shang, T., Zhuang, F., Shi, Z.: Parallel extreme learning machine for regression based on mapreduce. Neurocomputing 102, 52–58 (2013)CrossRefGoogle Scholar
  10. 10.
    Ishihata, M., Kameya, Y., Sato, T., Minato, S.: Propositionalizing the EM algorithm by BDDs. In: Late Breaking Papers of the 18th International Conference on Inductive Logic Programming (ILP 2008), pp. 44–49 (2008)Google Scholar
  11. 11.
    Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., van Kleef, P., Auer, S., Bizer, C.: DBpedia - a large-scale, multilingual knowledge base extracted from wikipedia. Semantic Web 6(2), 167–195 (2015)Google Scholar
  12. 12.
    Meng, X., Mahoney, M.: Robust regression on mapreduce. In: Proceedings of the 30th International Conference on Machine Learning, pp. 888–896. JMLR (2013)Google Scholar
  13. 13.
    Patel-Schneider, P., F., Horrocks, I., Bechhofer, S.: Tutorial on OWL (2003)Google Scholar
  14. 14.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Epistemic and statistical probabilistic ontologies. In: Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web. CEUR Workshop Proceedings, vol. 900, pp. 3–14. Sun SITE Central Europe (2012)Google Scholar
  15. 15.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Computing instantiated explanations in OWL DL. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds.) AI*IA 2013. LNCS, vol. 8249, pp. 397–408. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Parameter learning for probabilistic ontologies. In: Faber, W., Lembo, D. (eds.) RR 2013. LNCS, vol. 7994, pp. 265–270. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  17. 17.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Probabilistic description logics under the distribution semantics. Seman. Web 6(5), 447–501 (2015)Google Scholar
  18. 18.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Reasoning with probabilistic ontologies. In: Yang, Q., Wooldridge, M. (eds.) Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina, pp. 4310–4316. AAAI Press/International Joint Conferences on Artificial Intelligence, Palo Alto (2015)Google Scholar
  19. 19.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R., Cota, G.: Learning probabilistic description logics. In: Bobillo, F., et al. (eds.) URSW III. LNCS, vol. 8816, pp. 63–78. Springer, Heidelberg (2014)Google Scholar
  20. 20.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R., Cota, G.: Probabilistic logic programming on the web. Software Pract. and Exper (2016, to appear). http://ds.ing.unife.it/~friguzzi/Papers/RigBelLam-SPE16.pdf
  21. 21.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: BUNDLE: a reasoner for probabilistic ontologies. In: Faber, W., Lembo, D. (eds.) RR 2013. LNCS, vol. 7994, pp. 183–197. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  22. 22.
    Sato, T.: A statistical learning method for logic programs with distribution semantics. In: Sterling, L. (ed.) Proceedings of the Twelfth International Conference on Logic Programming, Tokyo, Japan, pp. 715–729. MIT Press (1995)Google Scholar
  23. 23.
    Sirin, E., Parsia, B., Cuenca-Grau, B., Kalyanpur, A., Katz, Y.: Pellet: a practical OWL-DL reasoner. J. Web Semant. 5(2), 51–53 (2007)CrossRefGoogle Scholar
  24. 24.
    Srinivasan, A., King, R.D., Muggleton, S., Sternberg, M.J.E.: Carcinogenesis predictions using ILP. In: Džeroski, S., Lavrač, N. (eds.) ILP 1997. LNCS, vol. 1297, pp. 273–287. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  25. 25.
    Srinivasan, A., Muggleton, S., Sternberg, M.J.E., King, R.D.: Theories for mutagenicity: A study in first-order and feature-based induction. Artif. Intell. 85(1–2), 277–299 (1996)CrossRefGoogle Scholar
  26. 26.
    Sun, Z., Fox, G.: Study on parallel svm based on mapreduce. In: Proceedings of the 18th International Conference on Parallel and Distributed Processing Techniques and Applications, pp. 16–19 (2012)Google Scholar
  27. 27.
    Zese, Riccardo, Bellodi, Elena, Lamma, Evelina, Riguzzi, Fabrizio, Aguiari, Fabiano: Semantics and inference for probabilistic description logics. In: Bobillo, Fernando, Carvalho, Rommel N., Costa, Paulo C.G., d’Amato, Claudia, Fanizzi, Nicola, Laskey, Kathryn B., Laskey, Kenneth J., Lukasiewicz, Thomas, Nickles, Matthias, Pool, Michael (eds.) URSW III. LNCS, vol. 8816, pp. 79–99. Springer, Heidelberg (2014)Google Scholar
  28. 28.
    Zese, R., Bellodi, E., Riguzzi, F., Lamma, E.: Tableau reasoners for probabilistic ontologies exploiting logic programming techniques. In: Bellodi, E., Bonfietti, A. (eds.) Proceedings of the Doctoral Consortium (DC) co-located with the 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015). CEUR Workshop Proceedings, vol. 1485, pp. 1–6. Sun SITE Central Europe, Aachen (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Giuseppe Cota
    • 1
  • Riccardo Zese
    • 1
  • Elena Bellodi
    • 1
  • Fabrizio Riguzzi
    • 2
  • Evelina Lamma
    • 1
  1. 1.Dipartimento di IngegneriaUniversity of FerraraFerraraItaly
  2. 2.Dipartimento di Matematica e InformaticaUniversity of FerraraFerraraItaly

Personalised recommendations