Skip to main content

Query Translation

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems
  • 153 Accesses

Synonyms

Query mapping; Query translation

Definition

Given a source query Qs over a source schema and a target query template over a target schema, query translation generates a query that is semantically closest to the source query and syntactically valid to the target schema. The semantically closest is measured by a closeness metrics, typically defined by precision and/or recall of a translated query Versus a source query over a database content. Syntax validness indicates the answerability of a translated query over the target schema. Therefore, the goal of query translation is to find a query that is answerable over the target schema and meanwhile retrieves the closest set of results as the source query would retrieve over a database content.

Historical Background

Query translation is an essential problem in any data integration system and has been studied extensively in the database area. Since a data integration system needs to integrate many different sources, query translation...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Chen-Chuan CK, Garcia-Molina H. Approximate query mapping: accounting for translation closeness. VLDB J. 2001;10(2–3):155–81.

    MATH  Google Scholar 

  2. Chen-Chuan CK, He B, Zhang Z. Toward large scale integration: building a metaquerier over databases on the web. In: Proceedings of the 2nd Biennial Conference on Innovative Data Systems Research; 2005. p. 44–55.

    Google Scholar 

  3. Doan A, Domingos P, Halevy AY. Reconciling schemas of disparate data sources: a machine-learning approach. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2001. p. 509–20.

    Google Scholar 

  4. Halevy AY. Answering queries using views: a survey. VLDB J. 2001;10(4):270–94.

    Article  MATH  Google Scholar 

  5. He B, Cheng-Chuan CK. Statistical schema matching across web query interfaces. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2003. p. 217–28.

    Google Scholar 

  6. He B, Cheng-Chuan CK, Han J. Discovering complex matchings across web query interfaces: a correlation mining approach. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2004. p. 148–57.

    Google Scholar 

  7. Kang J, Naughton JF. On schema matching with opaque column names and data values. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2003. p. 205–16.

    Google Scholar 

  8. Levy AY, Rajaraman A, Ordille JJ. Querying heterogeneous information sources using source descriptions. In: Proceedings of the 22th International Conference on Very Large Data Bases; 1996. p. 251–62.

    Google Scholar 

  9. Papakonstantinou Y, Gupta A, Garcia-Molina H, Ullman JD. A query translation scheme for rapid implementation of wrappers. In: Proceedings of the 4th International Conference on Deductive and Object-Oriented Databases; 1995. p. 161–86.

    Chapter  Google Scholar 

  10. Papakonstantinou Y, Gupta A, Haas L. Capabilities-based query rewriting in mediator systems. Proceedings of the 4th international conference on Parallel and distributed information systems; 1996. p. 170–81.

    Google Scholar 

  11. Rahm R, Bernstein PA. A survey of approaches to automatic schema matching. VLDB J. 2001;10(4): 334–50.

    Article  MATH  Google Scholar 

  12. Rajaraman A, Sagiv Y, Ullman JD. Answering queries using templates with binding patterns. In: Proceedings of the 14th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems; 1995. p. 105–12.

    Google Scholar 

  13. Vassalos V, Papakonstantinou Y. Expressive capabilities description languages and query rewriting algorithms. J Logic Program. 2000;43(1):75–122.

    Article  MathSciNet  MATH  Google Scholar 

  14. Wu W, Yu CT, Doan A, Meng W. An interactive clustering-based approach to integrating source query interfaces on the deep web. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2004. p. 95–106.

    Google Scholar 

  15. Zhang Z, He B, Chen-Chuan Chang K. Light-weight domain-based form assistant: querying web databases on the fly. In: Proceedings of the 31st International Conference on Very Large Data Bases; 2005. p. 97–108.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhen Zhang .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Zhang, Z. (2018). Query Translation. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1070

Download citation

Publish with us

Policies and ethics