Skip to main content
Springer Nature Link
Log in

Integrated Document Browsing and Data Acquisition for Building Large Ontologies

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4253))

  • 1266 Accesses

Abstract

Named entities (e.g., “Kofi Annan”, “Coca-Cola”, “Second World War”) are ubiquitous in web pages and other types of document and often provide a simplified picture of the document’s content. We present an ontology currently containing 31,000 named entities in different languages from various domains such as history, geography, politics, sports, arts, etc., which is being developed at the University of Munich (LMU). The underlying graph data model is simple and yet extremely versatile in different application scenarios. We demonstrate a prototype of a graphical interface to both the ontology and to documents on the web or in a local document repository, with a tight interaction in both directions. Occurrences of concepts from the ontology are highlighted and hyperlinked in the documents. Unrecognized entities could be added to the database and related to other concepts in a semiautomatic process. The entity database can also be used for extending full-text queries on the web or the repository to semantically close documents, and for indexing different kinds of named entities in the document repository. Similar to a programming IDE, the system illustrates how integrated browsing, search and update functionality contributes to the construction of high-quality ontologies, fundamental to the vision of a truly “semantic” web.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Dean, M., Schreiber, G.: OWL Web Ontology Language Ref., W3C Rec. (2005)

    Google Scholar 

  2. Klyne, G., Carroll, J.J.: Resource Description Framework, W3C Rec. (2005)

    Google Scholar 

  3. Sure, Y., Erdmann, M., Angele, J., Staab, S., Studer, R., Wenke, D.: OntoEdit: Collaborative Ontology Engineering for the Semantic Web. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 221–235. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. Noy, N.F., Sintek, M., et al.: Creating Semantic Web Contents with Protege-2000. IEEE Intelligent Systems 16, 60–71 (2001)

    Google Scholar 

  5. Wikipedia: The Free Encyclopedia, http://www.wikipedia.org

  6. Schulz, K.U., Weigel, F.: Systematics and architecture for a resource representing knowledge about named entities. In: Bry, F., Henze, N., Małuszyński, J. (eds.) PPSWR 2003. LNCS, vol. 2901, pp. 189–207. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  7. Brunner, L., Schulz, K.U., Weigel, F.: Organizing Thematic, Geographic and Temporal Knowledge in a Well-founded Navigation Space: Logical and Algorithmic Foundations for EFGT Nets. J. Web Serv. Research, Spec. Issue Semantically Augmented Metadata for Services, Grids, and Software Engin. (in press, 2006)

    Google Scholar 

  8. Mihov, S., Schulz, K.U.: Efficient Dictionary-Based Text Rewriting using Subsequential Transducers. Journal of Natural Language Engineering (2005)

    Google Scholar 

  9. Dzbor, M., Domingue, J., Motta, E.: Magpie – towards a semantic web browser. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 690–705. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Carr, L., Hall, W., Bechhofer, S., Goble, C.: Conceptual Linking: Ontology-based Open Hypermedia. In: Proc. 10th Int. World Wide Web Conf., pp. 334–342 (2001)

    Google Scholar 

  11. Cunningham, H., Humphreys, K., et al.: GATE – a General Architecture for Text Engineering. In: Proc. 5th Applied Natural Lang. Processing Conf., pp. 29–30 (1997)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Information and Language Processing (CIS), University of Munich (LMU), Germany

    Felix Weigel, Klaus U. Schulz, Levin Brunner & Eduardo Torres-Schumann

Authors
  1. Felix Weigel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Klaus U. Schulz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Levin Brunner
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eduardo Torres-Schumann
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Weigel, F., Schulz, K.U., Brunner, L., Torres-Schumann, E. (2006). Integrated Document Browsing and Data Acquisition for Building Large Ontologies. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893011_78

Download citation

  • DOI: https://doi.org/10.1007/11893011_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46542-3

  • Online ISBN: 978-3-540-46544-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics