Advertisement

Semantic Enrichment of Web Query Interfaces to Enable Dynamic Deep Linking to Web Information Portals

  • Arne Martin Klemenz
  • Klaus Tochtermann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10450)

Abstract

This article addresses how to improve the automated accessibility and visibility of information from Web Information Portals and in particular virtual library systems. Information from web information portals could provide great value to satisfy information needs. But most of this information stays hidden in data silos which are part of that section of the web that is not indexable by common search engines and is therefore called Deep Web. Shared vocabularies like Schema.org helped to increase machine readability of structured information on the web in general, but markup vocabularies didn’t increase the accessibility and visibility of information from data silos. This article addresses the limitations regarding the accessibility of information from data silos on the Deep Web and proposes an extension to Schema.org to fill the identified gaps. The extension improves the automated accessibility and visibility of information provided in web information portals by providing Dynamic Deep Linking capabilities to Deep Web data silos by lifting web forms of web information portals to the level of machine understandable semantic Web Query Interfaces.

Keywords

Dynamic Deep Linking Schema.org extension Web query interface Web information portals Virtual library systems 

References

  1. 1.
    Bergman, M.K.: White paper: the deep web: surfacing hidden value. J. Electron. Publish. 7(1), 1–17 (2001)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Blandford, A.: Google, public libraries, and the deep web. Dalhousie J. Interdiscip. Manage. 11 (2015)Google Scholar
  3. 3.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data-the story so far. In: Semantic Services, Interoperability and Web Applications: Emerging Concepts, pp. 205–227 (2009)Google Scholar
  4. 4.
    Ferrara, E., De Meo, P., Fiumara, G., Baumgartner, R.: Web data extraction, applications and techniques: a survey. Knowl.-Based Syst. 70, 301–323 (2014)CrossRefGoogle Scholar
  5. 5.
    Furche, T., Gottlob, G., Grasso, G., Guo, X., Orsi, G., Schallhart, C.: The ontological key: automatically understanding and integrating forms to access the deep Web. VLDB J. 22(5), 615–640 (2013)CrossRefGoogle Scholar
  6. 6.
    Henzinger, M.R.: Hyperlink analysis for the web. IEEE Internet Comp. 5(1), 45–50 (2001)CrossRefGoogle Scholar
  7. 7.
    Klemenz, A.M., Tochtermann, K.: Semantification of Query Interfaces to Improve Access to Deep Web Content. SDA, pp. 104–111 (2013)Google Scholar
  8. 8.
    Lanthaler, M., Gütl C.: Hydra: a vocabulary for hypermedia-driven web apis. In: LDOW, vol. 996 (2013)Google Scholar
  9. 9.
    Purcell, K., Brenner, J., Rainie L.: Search engine use 2012 (2012)Google Scholar
  10. 10.
    Van de Sompel, H., Beit-Arie, O.: Open linking in the scholarly information environment using the OpenURL framework. New Rev. Inf. Netw. 7(1), 59–76 (2001)CrossRefGoogle Scholar
  11. 11.
    Steiner, T., Troncy, R., Hausenblas, M.: How Google is using linked data today and vision for tomorrow. In: Proceedings of Linked Data in the Future Internet, vol. 700 (2010)Google Scholar
  12. 12.
    Wang, L., Hawbani, A., Wang, X.: Focused deep web entrance crawling by form feature classification. In: Wang, Yu., Xiong, H., Argamon, S., Li, X., Li, J. (eds.) BigCom 2015. LNCS, vol. 9196, pp. 79–87. Springer, Cham (2015). doi: 10.1007/978-3-319-22047-5_7 CrossRefGoogle Scholar
  13. 13.
    Zhang, Z., He, B., Chen-Chuan Chang, K.: Understanding web query interfaces: best-effort parsing with hidden syntax. In: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, pp. 107–118. ACM (2004)Google Scholar
  14. 14.
    Zhao, F., Zhou, J., Nie, C., Huang, H., Jin, H.: SmartCrawler: a two-stage crawler for efficiently harvesting deep-web interfaces. IEEE Trans. Serv. Comput. 9(4), 608–620 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.ZBW – Leibniz-Information Centre for EconomicsKielGermany

Personalised recommendations