Skip to main content

Web Search Query Rewriting

  • Reference work entry
  • 102 Accesses

Synonyms

Query reformulation; Query expansion; Query assistance; Query suggestion

Definition

Query rewriting in Web search refers to the process of reformulating an original input query to a new query in order to achieve better search results. Reformulation includes but not limited to the following:

  1. 1.

    Adding additional terms to express the search intent more accurately

  2. 2.

    Deleting redundant terms or re-weighting the terms in the original query to emphasize important terms

  3. 3.

    Finding alternative morphological forms of words by stemming each word, and searching for the alternative forms as well

  4. 4.

    Finding synonyms of words, and searching for the synonyms as well

  5. 5.

    Fixing spelling errors and automatically searching for the corrected form or suggesting it in the results

Historical Background

Web search queries are the words users type into web search engines to express their information need. These queries are typically 2–3 words long [7]. Traditional information retrieval allows...

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-0-387-39940-9_461
  • Chapter length: 3 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   2,500.00
Price excludes VAT (USA)
  • ISBN: 978-0-387-39940-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout

Recommended Reading

  1. Anick P. Using terminological feedback for Web search refinement – a log-based study. In Proc. 26th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2003, pp. 88–95.

    Google Scholar 

  2. Brill E. and Moore R.C. An improved error model for noisy channel spelling correction. In Proc. 38th Annual Meeting of the Assoc. for Computational Linguistics, 2000, pp. 86–293.

    Google Scholar 

  3. Croft W.B. and Harper D.J. Using probabilistic models of document retrieval without relevance information. J. Doc., 35(4):285–295, 1979.

    CrossRef  Google Scholar 

  4. Cucerzan S. and Brill E. Spelling correction as an iterative process that exploits the collective knowledge of Web users. In Proc. Conf. on Empirical Methods in Natural Language Processing, 2004, pp. 293–300.

    Google Scholar 

  5. Cui H., Wen J.R., Nie J.Y., and Ma W.Y. Probabilistic query expansion using query logs. In Proc. 11th Int. World Wide Web Conference, 2002, pp. 325–332.

    Google Scholar 

  6. Fonseca B.M., Golgher P., Pssas B., Ribeiro-Neto B., and Ziviani N. Concept-based interactive query expansion. In Proc. 14th ACM Int. Conf. on Information and Knowledge Management, 2008, pp. 696–703.

    Google Scholar 

  7. Jansen B.J., Spink A., and Saracevic T. Real life, real users, and real needs: a study and analysis of user queries on the web. Inf. Process. Manage. Int. J., 36(2):207–227, 2000.

    CrossRef  Google Scholar 

  8. Joachims T., Granka L., Pang B., Hembrooke H., and Gay G. Accurately interpreting clickthrough data as implicit feedback. In Proc. 31st Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2005, pp. 154–161.

    Google Scholar 

  9. Jones R. and Fain D. Query word deletion prediction. In Proc. 26th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2003, pp. 435–436.

    Google Scholar 

  10. Jones R., Rey B., Madani O., and Greiner W. Generating query substitutions. In Proc. 15th Int. World Wide Web Conference, 2006, pp. 387–396.

    Google Scholar 

  11. Lovins J.B. Development of a stemming algorithm. Mech. Translat. Comput. Ling., 2:22–31, 1968.

    Google Scholar 

  12. Peng F., Ahmed N., Li X., and Lu Y. Context sensitive stemming for Web search. In Proc. 33rd Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2007, pp. 639–646.

    Google Scholar 

  13. Porter M.F. An algorithm for suffix stripping. Program, 14(3):130–137, 1980.

    Google Scholar 

  14. Qiu Y. and Frei H.P. Concept based query expansion. In Proc. 16th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 1993, pp. 160–169.

    Google Scholar 

  15. Tan B. and Peng F. Unsupervised query segmentation using generative language models and wikipedia. In Proc. 17th Int. World Wide Web Conference, 2008, pp. 347–356.

    Google Scholar 

  16. Wei X., Peng F., and Dumoulin B. Analyzing Web text association to disambiguate abbreviation in queries. In Proc. 34th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2008, pp. 751–752.

    Google Scholar 

  17. Xu J. and Croft B. Query expansion using local and global document analysis. In Proc. 19th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 1996, pp. 4–11.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Jones, R., Peng, F. (2009). Web Search Query Rewriting. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_461

Download citation