skip to main content
10.1145/2452376.2452394acmotherconferencesArticle/Chapter ViewAbstractPublication PagesedbtConference Proceedingsconference-collections
research-article

Proactive natural language search engine: tapping into structured data on the web

Published:18 March 2013Publication History

ABSTRACT

In this era of "big data", a key challenge facing the database community is to help average users tap into the huge amounts of structured data on the Web. To address this challenge, we propose a novel proactive template-based engine for searching structured data on the Web using natural language. Departing from conventional search engines, the proposed engine organizes questions it can answer using templates and figures out ahead of time which sources can answer which templates and how. Then, at query time, the engine can simply match queries with the templates and retrieve answers using the pre-compiled evaluation plans. While attractive, building such an engine requires innovations in template creation, query evaluation, and system evolution. In this paper, we propose novel techniques to address these challenges.

References

  1. G. Agarwal et al. Towards rich query interpretation: walking back and forth for mining query templates. In WWW, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. R. Burke et al. Natural language processing in the faq finder system. In AAAI spring symposium, 1997.Google ScholarGoogle Scholar
  3. M. J. Cafarella et al. Webtables: exploring the power of tables on the web. PVLDB, 1(1), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. J. Carman et al. Learning semantic descriptions of web information sources. In IJCAI, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Y. Chen et al. Keyword search on structured and semi-structured data. In SIGMOD Conference, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. Doan, A. Halevy, and Z. Ives. Principles of Data Integration. Morgan Kaufmann, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. D. Gildea et al. Automatic labeling of semantic roles. Computational Linguistics, 28(3), 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. M. A. Hearst. Search User Interfaces. Cambridge University Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Y. Li et al. A domain-adaptive natural language interface for querying xml. In SIGMOD, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J. Madhavan et al. Web-scale data integration: You can afford to pay as you go. In CIDR, 2007.Google ScholarGoogle Scholar
  11. A. Nandi and H. V. Jagadish. Qunits: queried units in database search. In CIDR, 2009.Google ScholarGoogle Scholar
  12. National Science Foundation. NSF Award Search. http://www.nsf.gov/awardsearch/.Google ScholarGoogle Scholar
  13. E. Sadikov et al. Clustering query refinements by user intent. In WWW, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. N. Sarkas et al. Structured annotations of web queries. In SIGMOD, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. W. Shen et al. Toward best-effort information extraction. In SIGMOD, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. K. Tjin-Kam-Jet et al. Free-text search versus complex web forms. In ECIR, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. W. Wu et al. An interactive clustering-based approach to integrating source query interfaces on the deep web. In SIGMOD, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Proactive natural language search engine: tapping into structured data on the web

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Other conferences
            EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology
            March 2013
            793 pages
            ISBN:9781450315975
            DOI:10.1145/2452376

            Copyright © 2013 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 18 March 2013

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            Overall Acceptance Rate7of10submissions,70%

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader