Towards Aggregated Answers for Semistructured Data

  • Holger Meuss
  • Klaus U. Schulz
  • François Bry
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1973)


Semistructured data [5],[34],[23],[31],[1] are used to model data transferred on the Web for applications such as e-commerce [18], biomolecular biology [8], document management [2],[21], linguistics [32], thesauri and ontologies [17]. They are formalized as trees or more generally as (multi-)graphs [23],[1]. Query languages for semistructured data have been proposed [6],[11],[1],[4],[10] that, like SQL, can be seen as involving a number of variables [35], but, in contrast to SQL, give rise to arrange the variables in trees or graphs reflecting the structure of the semi- structured data to be retrieved. Leaving aside the “construct” parts of queries, answers can be formalized as mappings represented as tuples, hence called an- swer tuples, that assign database nodes to query variables. These answer tuples underly the semistructured data delivered as answers.


Query Language Target Candidate Evaluation Problem Conjunctive Query Query Path 
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.
    S. Abiteboul, P. Buneman, and D. Suciu. Data on the Web: From Relations to Semistructured Data and XML. Morgan Kaufmann Publishers, 2000.Google Scholar
  2. 2.
    R. Baeza-Yates and G. Navarro. Integrating contents and structure in text retrieval. SIGMOD Record, 25(1):67–79, 1996.CrossRefGoogle Scholar
  3. 4.
    A. Bonifati and S. Ceri. A comparative analysis of five XML query languages. SIGMOD Record, March 2000.Google Scholar
  4. 5.
    P. Buneman. Semistructured data. In Proc. ACM PODS’97, 1997.Google Scholar
  5. 6.
    S. Ceri, S. Comai, E. Damiani, P. Fraternali, S. Paraboschi, and L. Tanca. XML-GL: a graphical language for querying and restructuring XML documents. Computer Networks, 31(11-16):1171–1187, May 1999.Google Scholar
  6. 7.
    A. K. Chandra and P. M. Merlin. Optimal implementation of conjunctive queries in relational data bases. In Proc. 9th Annual ACM Symp. on Theory of Computing, 1977.Google Scholar
  7. 9.
    M. Consens and A. Mendelzon. Graphlog: a visual formalism of real life recursion. In Proc. ACM PODS’90, 1990.Google Scholar
  8. 10.
    A. Deutsch, M. Fernandez, D. Florescu, A. Levy, D. Maier, and D. Suciu. Querying XML data. IEEE Data Bulletin, 22(3):10–18, 1999.Google Scholar
  9. 11.
    A. Deutsch, M. Fernandez, D. Florescu, A. Levy, and D. Suciu. XML-QL: A query language for XML. Submission to the WWW Consortium:, August 1998.
  10. 12.
    M. Fernandez, J. Siméon, and P. Wadler. XML query languages: Experiences and exemplars. Draft,, 1999.
  11. 13.
    M. R. Garey and D. S. Johnson. Computers and Intractibility: A Guide to the Theory of NP-Completeness. W. H. Freeman and Company, New York, 1979.Google Scholar
  12. 14.
    R. Goldman and J. Widom. Dataguides: Enabling query formulation and optimization in semistructured databases. In Proc. VLDB’97, 1997.Google Scholar
  13. 15.
    R. Goldman and J. Widom. Interactive query and search in semistructured databases. In WebDB’98, Proc. Int. Workshop on the Web and Databases, 1998.Google Scholar
  14. 16.
    G. Gottlob, N. Leone, and F. Scarcello. The complexity of acyclic conjunctive queries. In Proc. 39th Annual Symp. on Foundations of Computer Science, 1998.Google Scholar
  15. 17.
    N. Guarino, editor. Int. Conf. on Formal Ontology in Information Systems. IOS Press, 1998.Google Scholar
  16. 18.
    A. Gupta. Some database issues in e-commerce. Invited talk at the Int. Conf. on Extending Database Theory,, 2000.
  17. 19.
    M. Gyssens, J. Paredaens, J. V. den Bussche, and D. V. Gucht. A graph-oriented object database model. IEEE Transactions on Knowledge and Data Engineering, 6(4):572–586, Aug. 1994.Google Scholar
  18. 20.
    P. Kilpeläinen. Tree Matching Problems with Applications to Structured Text Databases. PhD thesis, Dept. of Computer Science, University of Helsinki, 1992.Google Scholar
  19. 21.
    A. Loeffen. Text databases: A survey of text models and systems. SIGMOD Record, 23(1):97–106, Mar. 1994.Google Scholar
  20. 22.
    D. Maier. Database desiderata for an xml query language. In QL’98-The Query Languages Workshop, 1998.Google Scholar
  21. 23.
    J. McHugh, S. Abiteboul, R. Goldman, D. Quass, and J. Widom. Lore: A database management system for semistructured data. SIGMOD Record, 26(3), 1997.Google Scholar
  22. 24.
    H. Meuss. Logical Tree Matching with Complete Answer Aggregates for Retrieving Structured Documents. PhD thesis, Dept. of Computer Science, University of Munich, 2000.Google Scholar
  23. 25.
    H. Meuss and K. U. Schulz. Complete answer aggregates for structured document retrieval. Technical Report 98-112, CIS, University of Munich, 1998. Submitted.Google Scholar
  24. 26.
    H. Meuss, K. U. Schulz, and F. Bry. Towards aggregated answers for semistructured data. Technical report, Institute for Computer Science, University of Munich, 2000.
  25. 27.
    H. Meuss and C. Strohmaier. Improving index structures for structured document retrieval. In IRSG’99, 21st Annual Colloquium on IR Research, 1999.Google Scholar
  26. 28.
    T. Milo and D. Suciu. Index structures for path expressions. In ICDT’99, Proc. 6th Int. Conf. on DB Theory, 1999.Google Scholar
  27. 29.
    R. Mohr and T. C. Henderson. Arc and path consistency revisited. Artificial Intelligence, 28:225–233, 1986.CrossRefGoogle Scholar
  28. 30.
    F. Neven and T. Schwentick. Query automata. In PODS’99, 1999.Google Scholar
  29. 31.
    F. Neven and T. Schwentick. Expressive and efficient pattern languages for tree-structured data. In Proc. ACM PODS’00, 2000.Google Scholar
  30. 32.
    J. Oesterle and P. Maier-Meyer. The gnop (german noun phrase) treebank. In First International Conference on Language Resources and Evaluation, pages 699–703, 1998.Google Scholar
  31. 34.
    D. Suciu. An overview of semistructured data. SIGACT News, 29(4), 1998.Google Scholar
  32. 35.
    J. D. Ullman. Database and Knowledge-Base Systems, Volumes I and II. Computer Science Press, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Holger Meuss
    • 1
  • Klaus U. Schulz
    • 1
  • François Bry
    • 2
  1. 1.CIS, University of MunichMunichGermany
  2. 2.Institute for Computer ScienceUniversity of MunichMunichGermany

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