Skip to main content
SpringerLink
Log in

Metasearch Engines

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

  • 15 Accesses

Synonyms

Federated search engine

Definition

Metasearch is to utilize multiple other search systems (called component search systems) to perform simultaneous search. A metasearch engine is a search system that enables metasearch. To perform a basic metasearch, a user query is sent to multiple existing search engines by the metasearch engine; when the search results returned from the search engines are received by the metasearch engine, they are merged into a single ranked list and the merged list is presented to the user. Key issues include how to pass user queries to component search engines, how to extract correct search results from the result pages returned from component search engines, and how to merge the results returned from different component search sources. More sophisticated metasearch engines, especially those that have a large number of component search engines, also perform search engine selection (also referred to as database selection), i.e., identify the component...

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

Access this chapter

Log in via an institution
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. Aslam J, Montague M. Models for metasearch. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2001. p. 276–84.

    Google Scholar 

  2. Callan J, Lu Z, Croft, WB. Searching distributed collections with inference networks. In: Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 1995.

    Google Scholar 

  3. Callan J, Connell M, Du A. Automatic discovery of language models for text databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1999.

    Google Scholar 

  4. Chang CH, Kayed M, Girgis MR, Shaalan KF. A survey of web information extraction systems. IEEE Trans Knowl Data Eng. 2006;18(10):1411–28.

    Article  Google Scholar 

  5. Dreilinger D, Howe A. Experiences with selecting search engines using metasearch. ACM Trans Inf Sys. 1997;15(3):195–222.

    Article  Google Scholar 

  6. Lee JH. Combining multiple evidence from different properties of weighting schemes. In: Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 1995. p. 180–8.

    Google Scholar 

  7. Liu KL, Meng W, Qiu J, Yu C, Raghavan V, Wu Z, Lu Y, He H, Zhao H. AllInOneNews: development and evaluation of a large-scale news metasearch engine. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2007. p. 1017–28.

    Google Scholar 

  8. Liu W, Meng X, Meng W. ViDE: a vision-based approach for deep web data extraction. IEEE Trans Knowl Data Eng. 2010;22(3):447–60.

    Article  Google Scholar 

  9. Lu Y, Meng W, Shu L, Yu C, Liu K. Evaluation of result merging strategies for metasearch engines. In: Proceedings of the 6th International Conference on Web Information Systems Engineering; 2005. p. 53–66.

    Google Scholar 

  10. Meng W, Yu C. Advanced metasearch engine technology. Morgan & Claypool Publishers; 2010.

    Google Scholar 

  11. Meng W, Wu Z, Yu C, Li Z. A highly scalable and effective method for metasearch. ACM Trans on Inf Sys. 2001;19(3):310–35.

    Article  Google Scholar 

  12. Selberg E, Etzioni O. The MetaCrawler architecture for resource aggregation on the web. IEEE Expert. 1997;12(1):11–4.

    Article  Google Scholar 

  13. Shokouhi M, Si L. Federated search. Found Trends Info Retrieval. 2011;5(1):1–102.

    Article  Google Scholar 

  14. Sleiman HA, Corchuelo R. A survey on region extractors from web documents. IEEE Trans Knowl Data Eng. 2013;25(9):1960–81.

    Article  Google Scholar 

  15. Yu C, Liu K, Meng W, Wu Z, Rishe N. A methodology to retrieve text documents from multiple databases. IEEE Trans Knowl Data Eng. 2002;14(6):1347–61.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, USA

    Weiyi Meng

Authors
  1. Weiyi Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Weiyi Meng .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Google Research, New York, NY, USA

    Cong Yu

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

Meng, W. (2018). Metasearch Engines. 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_217

Download citation

Publish with us

Policies and ethics

Search

Navigation