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Controlled Aggregate Tree Shaped Questions over Ontologies

  • Camilo Thorne
  • Diego Calvanese
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5822)

Abstract

Controlled languages (CLs) are ambiguity-free subsets of natural languages such as English offering a good trade-off between the formal rigor of ontology and query languages and the intuitive appeal of natural language. They compositionally map (modulo a compositional translation τ(·)) into (or express) formal query languages and ontology languages. Modulo compositionality, they inherit the computational properties of such ontology/query languages. In the setting of OBDAS, we are interested in capturing query answering and measuring computational complexity w.r.t. the data queried (a.k.a. data complexity). In this paper we focus in defining a CL capable of expressing a subset SQL aggregate queries, and study its data complexity w.r.t. several ontology languages and extensions of the query language.

Keywords

Data Complexity Description Logic Query Language Aggregation Function Conjunctive Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Welsey, London (1995)zbMATHGoogle Scholar
  2. 2.
    Androutsopoulos, I., Ritchie, G.D., Thanisch, P.: Natural language interfaces to databases - an introduction. Journal of Natural Language Engineering 1(1), 29–81 (1995)CrossRefGoogle Scholar
  3. 3.
    Baader, F., Calvanese, D., Nardi, D., Patel-Schneider, P., McGuinness, D.: The Description Logic Handbook. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  4. 4.
    Bernardi, R., Calvanese, D., Thorne, C.: Lite natural language. In: IWCS 2007. Proceedings of the 7th International Workshop on Computational Semantics (2007)Google Scholar
  5. 5.
    Bernstein, A., Kaufmann, E., Göhring, A., Kiefer, C.: Querying ontologies: A controlled english interface for end-users. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 112–126. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Calvanese, D., de Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Data complexity of query answering in description logics. In: KR 2006. Proceedings of the 10th International Conference on the Principles of Knowledge Representation and Reasoning (2006)Google Scholar
  7. 7.
    Calvanese, D., Nutt, W., Kharlamov, E., Thorne, C.: Aggregate queries over ontologies. In: ONISW 2008. Proceedings 2nd International Workshop on Ontologies and Information Systems for the Semantic Web (2008)Google Scholar
  8. 8.
    Clifford, J.: Natural language querying of historical databases. Computational Linguistics 14(4), 10–35 (1988)Google Scholar
  9. 9.
    Fuchs, N.E., Kaljurand, K.: Mapping Attempto Controlled English to OWL DL. In: ESWC 2006. Demos and Posters of the 3rd European Semantic Web Conference (2006)Google Scholar
  10. 10.
    Jurafsky, D., Martin, J.: Speech and Language Processing. Prentice Hall, Englewood Cliffs (2000)Google Scholar
  11. 11.
    Mador-Haim, S., Winter, Y., Braun, A.: Controlled language for geographical information system queries. In: ICos5. Proceedings of the 5th International Workshop on Inference in Computational Semantics (2006)Google Scholar
  12. 12.
    Montague, R.: Universal grammar. Theoria 36(3), 373–398 (1970)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Pratt, I.: Data complexity of the two-variable fragment with counting quantifiers. Information and Computation 207(8), 867–888 (2009)zbMATHCrossRefMathSciNetGoogle Scholar
  14. 14.
    Pratt, I., Third, A.: More fragments of language. Notre Dame Journal of Formal Logic 47(2), 151–177 (2006)zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Schaerf, A.: On the complexity of the instance checking problem in concept languages with existential quantification. Journal of Intelligent Information Systems 2(3), 265–278 (1993)CrossRefMathSciNetGoogle Scholar
  16. 16.
    Staab, S., Studer, R. (eds.): Handbook on Ontologies. International Handbooks on Information Systems. Springer, Heidelberg (2004)Google Scholar
  17. 17.
    Thorne, C., Calvanese, D.: Exploring ontology-based data access. In: CNL 2009. Proceedings of the Workshop on Controlled Natural Language (2009)Google Scholar
  18. 18.
    Vardi, M.: The complexity of relational query languages. In: Proceedings of the Fourteenth Annual ACM Symposium on Theory of Computing (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Camilo Thorne
    • 1
  • Diego Calvanese
    • 1
  1. 1.KRDB CentreFree University of Bozen-BolzanoItaly

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