Semantic Web Search and Inductive Reasoning

  • Claudia d’Amato
  • Nicola Fanizzi
  • Bettina Fazzinga
  • Georg Gottlob
  • Thomas Lukasiewicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7123)

Abstract

Extensive research activities are recently directed towards the Semantic Web as a future form of the Web. Consequently, Web search as the key technology of the Web is evolving towards some novel form of Semantic Web search. A very promising recent such approach is based on combining standard Web pages and search queries with ontological background knowledge, and using standard Web search engines as the main inference motor of Semantic Web search. In this paper, we further enhance this approach to Semantic Web search by the use of inductive reasoning techniques. This adds especially the important ability to handle inconsistencies, noise, and incompleteness, which are all very likely to occur in distributed and heterogeneous environments, such as the Web. We report on a prototype implementation of the new approach and experimental results.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aarts, E., Korst, J., Michiels, W.: Simulated annealing. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies, ch. 7, pp. 187–210. Springer (2005)Google Scholar
  2. 2.
    Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook. Cambridge University Press (2003)Google Scholar
  3. 3.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Sci. Am. 284, 34–43 (2001)CrossRefGoogle Scholar
  4. 4.
    Bloehdorn, S., Sure, Y.: Kernel Methods for Mining Instance Data in Ontologies. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 58–71. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Borgida, A., Walsh, T.J., Hirsh, H.: Towards measuring similarity in description logics. In: Proc. DL 2005. CEUR Workshop Proceedings, vol. 147. CEUR-WS.org (2005)Google Scholar
  6. 6.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Comput. Netw. 30(1-7), 107–117 (1998)Google Scholar
  7. 7.
    Buitelaar, P., Cimiano, P.: Ontology Learning and Population: Bridging the Gap Between Text and Knowledge. IOS Press (2008)Google Scholar
  8. 8.
    Cheng, G., Ge, W., Qu, Y.: Falcons: Searching and browsing entities on the Semantic Web. In: Proc. WWW 2008, pp. 1101–1102. ACM Press (2008)Google Scholar
  9. 9.
    Chirita, P.-A., Costache, S., Nejdl, W., Handschuh, S.: P-TAG: Large scale automatic generation of personalized annotation TAGs for the Web. In: Proc. WWW 2007, pp. 845–854. ACM Press (2007)Google Scholar
  10. 10.
    Cimiano, P., Haase, P., Heizmann, J., Mantel, M., Studer, R.: Towards portable natural language interfaces to knowledge bases — The case of the ORAKEL system. Data Knowl. Eng. 65(2), 325–354 (2008)CrossRefGoogle Scholar
  11. 11.
    Cohen, W.W., Hirsh, H.: Learning the CLASSIC description logic. In: Proc. KR 1994, pp. 121–133. Morgan Kaufmann (1994)Google Scholar
  12. 12.
    Corby, O., Dieng-Kuntz, R., Faron-Zucker, C.: Querying the Semantic Web with Corese search engine. In: Proc. ECAI 2004, pp. 705–709. IOS Press (2004)Google Scholar
  13. 13.
    Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines. Cambridge University Press (2000)Google Scholar
  14. 14.
    d’Amato, C., Fanizzi, N., Esposito, F.: Query Answering and Ontology Population: An Inductive Approach. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 288–302. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    d’Amato, C., Staab, S., Fanizzi, N.: On the Influence of Description Logics Ontologies on Conceptual Similarity. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 48–63. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  16. 16.
    Damljanovic, D., Agatonovic, M., Cunningham, H.: Natural Language Interfaces to Ontologies: Combining Syntactic Analysis and Ontology-Based Lookup through the User Interaction. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part I. LNCS, vol. 6088, pp. 106–120. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    d’Aquin, M., Lieber, J., Napoli, A.: Decentralized Case-Based Reasoning for the Semantic Web. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 142–155. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Ding, L., Finin, T.W., Joshi, A., Peng, Y., Pan, R., Reddivari, P.: Search on the Semantic Web. IEEE Computer 38(10), 62–69 (2005)CrossRefGoogle Scholar
  19. 19.
    Fanizzi, N., d’Amato, C., Esposito, F.: Evolutionary conceptual clustering based on induced pseudo-metrics. Int. J. Semantic Web Inf. Syst. 4(3), 44–67 (2008)CrossRefGoogle Scholar
  20. 20.
    Fanizzi, N., d’Amato, C., Esposito, F.: Induction of classifiers through non-parametric methods for approximate classification and retrieval with ontologies. Int. J. Semant. Comput. 2(3), 403–423 (2008)MATHCrossRefGoogle Scholar
  21. 21.
    Fanizzi, N., d’Amato, C., Esposito, F.: Metric-based stochastic conceptual clustering for ontologies. Inform. Syst. 34(8), 725–739 (2009)CrossRefGoogle Scholar
  22. 22.
    Fazzinga, B., Gianforme, G., Gottlob, G., Lukasiewicz, T.: Semantic Web search based on ontological conjunctive queries. J. Web Sem. 9(4), 453–473 (2011)CrossRefGoogle Scholar
  23. 23.
    Fazzinga, B., Lukasiewicz, T.: Semantic search on the Web. Sem. Web 1(1/2), 89–96 (2010)Google Scholar
  24. 24.
    Fernández, M., Lopez, V., Sabou, M., Uren, V.S., Vallet, D., Motta, E., Castells, P.: Semantic search meets the Web. In: Proc. ICSC 2008, pp. 253–260. IEEE Computer Society (2008)Google Scholar
  25. 25.
    Finin, T.W., Ding, L., Pan, R., Joshi, A., Kolari, P., Java, A., Peng, Y.: Swoogle: Searching for knowledge on the Semantic Web. In: Proc. AAAI 2005, pp. 1682–1683. AAAI Press/MIT Press (2005)Google Scholar
  26. 26.
  27. 27.
    Guha, R.V., McCool, R., Miller, E.: Semantic search. In: Proc. WWW 2003, pp. 700–709. ACM Press (2003)Google Scholar
  28. 28.
    Haase, P., van Harmelen, F., Huang, Z., Stuckenschmidt, H., Sure, Y.: A Framework for Handling Inconsistency in Changing Ontologies. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 353–367. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  29. 29.
    Harth, A., Hogan, A., Delbru, R., Umbrich, J., O’Riain, S., Decker, S.: SWSE: Answers before links! In: Proc. Semantic Web Challenge 2007. CEUR Workshop Proceedings, vol. 295. CEUR-WS.org (2007)Google Scholar
  30. 30.
    Heflin, J., Hendler, J.A., Luke, S.: SHOE: A blueprint for the Semantic Web. In: Fensel, D., Wahlster, W., Lieberman, H. (eds.) Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential, pp. 29–63. MIT Press (2003)Google Scholar
  31. 31.
    Hitzler, P., Vrandečić, D.: Resolution-Based Approximate Reasoning for OWL DL. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 383–397. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  32. 32.
    Hu, B., Kalfoglou, Y., Alani, H., Dupplaw, D., Lewis, P.H., Shadbolt, N.: Semantic Metrics. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 166–181. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  33. 33.
    Iannone, L., Palmisano, I., Fanizzi, N.: An algorithm based on counterfactuals for concept learning in the Semantic Web. Int. J. Appl. Intell. 26(2), 139–159 (2007)CrossRefGoogle Scholar
  34. 34.
    Janowicz, K., Wilkes, M.: SIM-DLA: A Novel Semantic Similarity Measure for Description Logics Reducing Inter-concept to Inter-instance Similarity. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 353–367. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  35. 35.
    Kasneci, G., Suchanek, F.M., Ifrim, G., Ramanath, M., Weikum, G.: NAGA: Searching and ranking knowledge. In: Proc. ICDE 2008, pp. 953–962. IEEE Computer Society (2008)Google Scholar
  36. 36.
    Kietz, J.U., Morik, K.: A polynomial approach to the constructive induction of structural knowledge. Mach. Learn. 14, 193–218 (1994)MATHCrossRefGoogle Scholar
  37. 37.
    Lehmann, J., Hitzler, P.: Foundations of Refinement Operators for Description Logics. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds.) ILP 2007. LNCS (LNAI), vol. 4894, pp. 161–174. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  38. 38.
    Lei, Y., Uren, V.S., Motta, E.: SemSearch: A Search Engine for the Semantic Web. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 238–245. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  39. 39.
    Lopez, V., Pasin, M., Motta, E.: AquaLog: An Ontology-Portable Question Answering System for the Semantic Web. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 546–562. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  40. 40.
    Lopez, V., Sabou, M., Motta, E.: PowerMap: Mapping the Real Semantic Web on the Fly. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 414–427. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  41. 41.
    Mitchell, T.: Machine Learning. McGraw Hill (1997)Google Scholar
  42. 42.
    Nienhuys-Cheng, S.-H.: Distances and Limits on Herbrand Interpretations. In: Page, D.L. (ed.) ILP 1998. LNCS, vol. 1446, pp. 250–260. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  43. 43.
    Nováček, V., Groza, T., Handschuh, S.: CORAAL – Towards Deep Exploitation of Textual Resources in Life Sciences. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds.) AIME 2009. LNCS, vol. 5651, pp. 206–215. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  44. 44.
    Oren, E., Guéret, C., Schlobach, S.: Anytime Query Answering in RDF through Evolutionary Algorithms. In: Sheth, A.P., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 98–113. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  45. 45.
    Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R.: Linking Data to Ontologies. In: Spaccapietra, S. (ed.) Journal on Data Semantics X. LNCS, vol. 4900, pp. 133–173. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  46. 46.
    Schölkopf, B., Smola, A.J.: Learning with Kernels. MIT Press (2002)Google Scholar
  47. 47.
    Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: A core of semantic knowledge. In: Proc. WWW 2007, pp. 697–706. ACM Press (2007)Google Scholar
  48. 48.
    Thomas, E., Pan, J.Z., Sleeman, D.H.: ONTOSEARCH2: Searching ontologies semantically. In: Proc. OWLED 2007. CEUR Workshop Proceedings, vol. 258. CEUR-WS.org (2007)Google Scholar
  49. 49.
    Tran, T., Cimiano, P., Rudolph, S., Studer, R.: Ontology-Based Interpretation of Keywords for Semantic Search. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 523–536. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  50. 50.
    Tummarello, G., Cyganiak, R., Catasta, M., Danielczyk, S., Delbru, R., Decker, S.: Sig.ma: Live views on the Web of data. In: Proc. WWW 2010, pp. 1301–1304. ACM Press (2010)Google Scholar
  51. 51.
    Zenz, G., Zhou, X., Minack, E., Siberski, W., Nejdl, W.: From keywords to semantic queries — Incremental query construction on the Semantic Web. J. Web Sem. 7(3), 166–176 (2009)CrossRefGoogle Scholar
  52. 52.
    Zezula, P., Amato, G., Dohnal, V., Batko, M.: Similarity Search — The Metric Space Approach. Advances in Database Systems, vol. 32. Springer (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Claudia d’Amato
    • 1
  • Nicola Fanizzi
    • 1
  • Bettina Fazzinga
    • 2
  • Georg Gottlob
    • 3
    • 4
  • Thomas Lukasiewicz
    • 3
  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariItaly
  2. 2.Dipartimento di Elettronica, Informatica e SistemisticaUniversità della CalabriaItaly
  3. 3.Department of Computer ScienceUniversity of OxfordUK
  4. 4.Oxford-Man Institute of Quantitative FinanceUniversity of OxfordUK

Personalised recommendations