Skip to main content

Information Extraction from Webpages Based on DOM Distances

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7182))

Abstract

Retrieving information from Internet is a difficult task as it is demonstrated by the lack of real-time tools able to extract information from webpages. The main cause is that most webpages in Internet are implemented using plain (X)HTML which is a language that lacks structured semantic information. For this reason much of the efforts in this area have been directed to the development of techniques for URLs extraction. This field has produced good results implemented by modern search engines. But, contrarily, extracting information from a single webpage has produced poor results or very limited tools. In this work we define a novel technique for information extraction from single webpages or collections of interconnected webpages. This technique is based on DOM distances to retrieve information. This allows the technique to work with any webpage and, thus, to retrieve information online. Our implementation and experiments demonstrate the usefulness of the technique.

This work has been partially supported by the Spanish Ministerio de Ciencia e Innovación under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant PROMETEO/2011/052.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dalvi, B., Cohen, W.W., Callan, J.: Websets: Extracting sets of entities from the web using unsupervised information extraction. Technical report, Carnegie Mellon School of computer Science (2011)

    Google Scholar 

  2. Kushmerick, N., Weld, D.S., Doorenbos, R.: Wrapper induction for information extraction. In: Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI 1997) (1997)

    Google Scholar 

  3. Cohen, W.W., Hurst, M., Jensen, L.S.: A flexible learning system for wrapping tables and lists in html documents. In: Proceedings of the international World Wide Web conference (WWW 2002), pp. 232–241 (2002)

    Google Scholar 

  4. Lee, P.Y., Hui, S.C., Fong, A.C.M.: Neural networks for web content filtering. IEEE Intelligent Systems 17(5), 48–57 (2002)

    Article  Google Scholar 

  5. Anti-Porn Parental Controls Software. Porn Filtering (March 2010), http://www.tueagles.com/anti-porn/

  6. Kang, B.-Y., Kim, H.-G.: Web page filtering for domain ontology with the context of concept. IEICE - Trans. Inf. Syst. E90, D859–D862 (2007)

    Article  Google Scholar 

  7. Henzinger, M.: The Past, Present and Future of Web Information Retrieval. In: Proceedings of the 23th ACM Symposium on Principles of Database Systems (2004)

    Google Scholar 

  8. W3C Consortium. Resource Description Framework (RDF), www.w3.org/RDF

  9. W3C Consortium. Web Ontology Language (OWL), www.w3.org/2004/OWL

  10. Microformats.org. The Official Microformats Site (2009), http://microformats.org

  11. Khare, R., Çelik, T.: Microformats: a Pragmatic Path to the Semantic Web. In: Proceedings of the 15h International Conference on World Wide Web, pp. 865–866 (2006)

    Google Scholar 

  12. Khare, R.: Microformats: The Next (Small) Thing on the Semantic Web? IEEE Internet Computing 10(1), 68–75 (2006)

    Article  Google Scholar 

  13. Gupta, S., et al.: Automating Content Extraction of HTML Documents. World Wide Archive 8(2), 179–224 (2005)

    Article  Google Scholar 

  14. Li, P., Liu, M., Lin, Y., Lai, Y.: Accelerating Web Content Filtering by the Early Decision Algorithm. IEICE Transactions on Information and Systems E91-D, 251–257 (2008)

    Article  Google Scholar 

  15. W3C Consortium, Document Object Model (DOM), www.w3.org/DOM

  16. Baeza-Yates, R., Castillo, C.: Crawling the Infinite Web: Five Levels Are Enough. In: Leonardi, S. (ed.) WAW 2004. LNCS, vol. 3243, pp. 156–167. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  17. Micarelli, A., Gasparetti, F.: Adaptative Focused Crawling. In: The Adaptative Web, pp. 231–262 (2007)

    Google Scholar 

  18. Nielsen, J.: Designing Web Usability: The Practice of Simplicity. New Riders Publishing, Indianapolis (2010) ISBN 1-56205-810-X

    Google Scholar 

  19. Zhang, J.: Visualization for Information Retrieval. The Information Retrieval Series. Springer, Heidelberg (2007) ISBN 3-54075-1475

    Google Scholar 

  20. Hearst, M.A.: TileBars: Visualization of Term Distribution Information. In: Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, Denver, CO, pp. 59–66 (May 1995)

    Google Scholar 

  21. Gottron, T.: Evaluating Content Extraction on HTML Documents. In: Proceedings of the 2nd International Conference on Internet Technologies and Applications, pp. 123–132 (2007)

    Google Scholar 

  22. Apache Foundation. The Apache crawler Nutch (2010), http://nutch.apache.org

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Castillo, C., Valero, H., Ramos, J.G., Silva, J. (2012). Information Extraction from Webpages Based on DOM Distances. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28601-8_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28601-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28600-1

  • Online ISBN: 978-3-642-28601-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics