Creation, Population and Preprocessing of Experimental Data Sets for Evaluation of Applications for the Semantic Web

  • György Frivolt
  • Ján Suchal
  • Richard Veselý
  • Peter Vojtek
  • Oto Vozár
  • Mária Bieliková
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4910)

Abstract

In this paper we describe the process of experimental ontology data set creation. Such a semantically enhanced data set is needed in experimental evaluation of applications for the Semantic Web. Our research focuses on various levels of the process of data set creation – data acquisition using wrappers, data preprocessing on the ontology instance level and adjustment of the ontology according to the nature of the evaluation step. Web application aimed at clustering of ontology instances is utilized in the process of experimental evaluation, serving both as an example of an application and visual presentation of the experimental data set to the user.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Pinto, H.S., Peralta, D.: Combining Ontology Engineering Subprocesses to Build a Time Ontology. In: K-CAP 2003, pp. 88–95. ACM Press, New York (2003)CrossRefGoogle Scholar
  2. 2.
    Čerešňa, M.: Interactive Learning of HTML Wrappers Using Attribute Classification. In: Proc. of the First Int. Workshop on Representation and Analysis of Web Space, Prague, Czech Republic, pp. 137–142 (2005)Google Scholar
  3. 3.
    Kushmerick, N.: Wrapper Induction: Efficiency and expressiveness. Artificial Intelligence 118(1), 15–68 (2000)MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Simon, K., Lausen, G.: ViPER: Augmenting Automatic Information Extraction with Visual Perceptions. In: CIKM 2005, pp. 381–388. ACM Press, New York (2005)CrossRefGoogle Scholar
  5. 5.
    Weinstein, P.C., Birmingham, W.P.: Comparing Concepts in Differentiated Ontologies. In: KAW 1999 (1999)Google Scholar
  6. 6.
    Andrejko, A., Barla, M., Tvarožek, M.: Comparing Ontological Concepts to Evaulate Similarity. In: Návrat, P., et al. (eds.) Tools For Acquisition, Organisation and Presenting of Information and Knowledge, STU, pp. 71–78 (2006)Google Scholar
  7. 7.
    Rado, L.: Sharing of Research Results on Portal based on Semantic Web. Master’s thesis project report, Bieliková, M. (supervisor), Slovak University of Technology in Bratislava (2007)Google Scholar
  8. 8.
    Tvarožek, M., Bieliková, M.: Adaptive Faceted Browser for Navigation in Open Information Spaces. In: WWW 2007, pp. 1311–1312. ACM Press, New York (2007)CrossRefGoogle Scholar
  9. 9.
    Beckett, D.: Redland RDF Storage and Retrieval. In: SWAD-Europe Workshop on Semantic Web Storage and Retrieval (2004)Google Scholar
  10. 10.
    Hinton, G., Sejnowski, T.J.: Unsupervised Learning and Map Formation: Foundations of Neural Computation. MIT Press, Cambridge (1999)Google Scholar
  11. 11.
    Frivolt, G., Pok, O.: Comparison of Graph Clustering Approaches. In: Bieliková, M. (ed.) IIT.SRC 2006, Bratislava, Slovakia, pp. 168–175 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • György Frivolt
    • 1
  • Ján Suchal
    • 1
  • Richard Veselý
    • 1
  • Peter Vojtek
    • 1
  • Oto Vozár
    • 1
  • Mária Bieliková
    • 1
  1. 1.Institute of Informatics and Software Engineering, Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

Personalised recommendations