Skip to main content

Meta-search and Multi-domain Search

  • Chapter
Web Information Retrieval

Abstract

While search engine technology based on crawling and indexing, presented in Part II, dominates the market, a niche is open for search systems based on data integration technology. These systems either rely on other search engines as sources of information or directly access specialized data sources that are focused on given domains. Interest in such systems is growing with the increase of Web applications which offer simple query interfaces to domain-specific data sources. This chapter overviews the theory of rank-driven data integration and top-k query processing, and then focuses on meta-search and multi-domain search.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 79.99
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

Notes

  1. 1.

    The white paper can be retrieved from http://www.dogpile.com/info.dogpl/support/metasearch.

References

  1. A. Abid, M. Tagliasacchi, Top-k query processing with parallel probing of data sources, in SEBD, ed. by G. Mecca, S. Greco (2011), p. 155

    Google Scholar 

  2. J. Barker, C. Hennesy, Meta-search engines (2012), http://www.lib.berkeley.edu/TeachingLib/Guides/Internet/MetaSearch.html

  3. A. Bozzon, M. Brambilla, S. Ceri, P. Fraternali, Liquid query: multi-domain exploratory search on the web, in WWW, ed. by M. Rappa, P. Jones, J. Freire, S. Chakrabarti (ACM, New York, 2010), pp. 161–170

    Google Scholar 

  4. D. Braga, S. Ceri, F. Daniel, D. Martinenghi, Optimization of multi-domain queries on the web. Proc. VLDB Endow. 1(1), 562–573 (2008)

    Google Scholar 

  5. S. Ceri, M. Brambilla (eds.), Search Computing—Trends and Developments [Outcome of the Second SeCO Workshop on Search Computing, Como/Milan, Italy, May 25–31, 2010]. Lecture Notes in Computer Science, vol. 6585 (Springer, Berlin, 2011)

    Google Scholar 

  6. S. Ceri, D. Braga, M. Brambilla, A. Campi, E. Della Valle, P. Fraternali, D. Martinenghi, M. Tagliasacchi, Method for extracting, merging and ranking search engine results, US Patent US 8,180,768 B2, May, 2012. http://www.google.com/patents/US8180768

  7. R. Fagin, A. Lotem, M. Naor, Optimal aggregation algorithms for middleware, in PODS, ed. by P. Buneman (ACM, New York, 2001)

    Google Scholar 

  8. B. Fazzinga, T. Lukasiewicz, Semantic search on the web. Semant. Web 1(1), 89–96 (2010)

    Google Scholar 

  9. F. Giunchiglia, U. Kharkevich, I. Zaihrayeu, Concept search, in ESWC, ed. by L. Aroyo, P. Traverso, F. Ciravegna, P. Cimiano, T. Heath, E. Hyvönen, R. Mizoguchi, E. Oren, M. Sabou, E.P.B. Simperl Lecture Notes in Computer Science, vol. 5554 (Springer, Berlin, 2009), pp. 429–444

    Google Scholar 

  10. J. Hoffart, F.M. Suchanek, K. Berberich, E. Lewis-Kelham, G. de Melo, G. Weikum, YAGO2: exploring and querying world knowledge in time, space, context, and many languages, in WWW (Companion Volume), ed. by S. Srinivasan, K. Ramamritham, A. Kumar, M.P. Ravindra, E. Bertino, R. Kumar (ACM, New York, 2011), pp. 229–232

    Google Scholar 

  11. I.F. Ilyas, W.G. Aref, A.K. Elmagarmid, Supporting top-k join queries in relational databases. VLDB J. 13(3), 207–221 (2004)

    Article  Google Scholar 

  12. G. Marchionini, Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006)

    Article  Google Scholar 

  13. D. Martinenghi, M. Tagliasacchi, Top-k pipe join, in ICDE Workshops (IEEE Press, San Diego, 2010), pp. 16–19

    Google Scholar 

  14. S. Quarteroni, Question answering, semantic search and data service querying, in Proceedings of the KRAQ11 Workshop (Asian Federation of Natural Language Processing, Chiang Mai, 2011), pp. 10–17

    Google Scholar 

  15. S. Quarteroni, M. Brambilla, S. Ceri, A bottom-up, knowledge-aware approach to the integration of web data services, in ACM-TWEB. To appear

    Google Scholar 

  16. A. Rajaraman, Kosmix: high-performance topic exploration using the deep web. Proc. VLDB Endow. 2(2), 1524–1529 (2009)

    MathSciNet  Google Scholar 

  17. R.W. White, R.A. Roth, Exploratory Search: Beyond the Query-Response Paradigm. Synthesis Lectures on Information Concepts, Retrieval, and Services (Morgan & Claypool Publishers, San Rafael, 2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Ceri, S., Bozzon, A., Brambilla, M., Della Valle, E., Fraternali, P., Quarteroni, S. (2013). Meta-search and Multi-domain Search. In: Web Information Retrieval. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39314-3_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39314-3_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39313-6

  • Online ISBN: 978-3-642-39314-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics