Preferentially Annotated Regular Path Queries

  • Gösta Grahne
  • Alex Thomo
  • William Wadge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4353)


In this paper, we introduce preferential regular path queries. These are regular path queries whose symbols are annotated with preference weights for “scaling” up or down the intrinsic importance of matching a symbol against a (semistructured) database edge label. Annotated regular path queries are expressed syntactically as annotated regular expressions. We interpret these expressions in a uniform semiring framework, which allows different semantics specializations for the same syntactic annotations. For our preference queries, we study three important aspects: (1) (progressive) query answering (2) (certain) query answering in LAV data-integration systems, and (3) query containment and equivalence. In all of these, we obtain important positive results, which encourage the use of our preference framework for enhanced querying of semistructured databases.


Regular Expression Query Answer Query Answering Semistructured Data Preference Semantic 
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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  1. 1.
    Abiteboul, S., Buneman, P., Suciu, D.: Data on the Web: From Relations to Semistructured Data and XML. Morgan Kaufmann, San Francisco (1999)Google Scholar
  2. 2.
    Calvanese, D., Giacomo, G., Lenzerini, M., Vardi, M.Y.: Answering Regular Path Queries Using Views. In: Proc. of ICDE 2000 (2000)Google Scholar
  3. 3.
    Calvanese, D., Giacomo, G., Lenzerini, M., Vardi, M.Y.: View-based Query Processing: On the Relationship between Rewriting, Answering and Losslessness. In: Eiter, T., Libkin, L. (eds.) ICDT 2005. LNCS, vol. 3363, Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Chomicki, J.: Preference formulas in relational queries. ACM Trans. Database Syst. 28(4), 427–466 (2003)CrossRefGoogle Scholar
  5. 5.
    Flesca, S., Furfaro, F., Greco, S.: Weighted Path Queries on Web Data. In: Proc. of WebDB 2001 (2001)Google Scholar
  6. 6.
    Grahne, G., Thomo, A.: Query Answering and Containment for Regular Path Queries under Distortions. In: Seipel, D., Turull-Torres, J.M.a. (eds.) FoIKS 2004. LNCS, vol. 2942, Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Grahne, G., Thomo, A., Wadge, W.: Preferentially Annotated Regular Path Queries,
  8. 8.
    Hashiguchi, K.: Limitedness Theorem on Finite Automata with Distance Functions. Journal of Computer and System Sciences 24(2), 233–244 (1982)zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Kiesling, W., Hafenrichter, B., Fischer, S., Holland, S.: Preference XPATH – A query language for E-commerce. In: Proc. of the 5th Int’l Conf. Wirtschaftsinformatik, Augsburg, Germany (2001)Google Scholar
  10. 10.
    Lenzerini, M.: Data Integration: A Theoretical Perspective. In: Proc. of PODS 2002 (2002)Google Scholar
  11. 11.
    Ruchi, A.: A Framework for Expressing Prioritized Constraints Using Infinitesimal Logic Master Thesis University of Victoria, BC, Canada (2005)Google Scholar
  12. 12.
    Stefanescu, D.C., Thomo, A., Thomo, L.: Distributed evaluation of generalized path queries. In: Proc. of SAC 2005 (2005)Google Scholar
  13. 13.
    Stefanescu, D.C., Thomo, A.: Enhanced Regular Path Queries on Semistructured Databases. In: Proc. of QLQP 2005 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gösta Grahne
    • 1
  • Alex Thomo
    • 2
  • William Wadge
    • 2
  1. 1.Concordia UniversityMontrealCanada
  2. 2.University of VictoriaVictoriaCanada

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