Improving Semantic Search Via Integrated Personalized Faceted and Visual Graph Navigation

  • Michal Tvarožek
  • Michal Barla
  • György Frivolt
  • Marek Tomša
  • Mária Bieliková
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4910)


Growing need for information retrieval, information processing, and the associated need for navigation in existing information spaces resulted in several approaches that aim to improve efficiency of the respective user tasks. However, problems related to user navigation and orientation in large open information spaces still persist possibly due to increasing demands and the imperfections of individual approaches. We propose an integrated search and navigation solution that takes advantage of the faceted browsing paradigm and visual navigation in graphs both extended with support for automatic personalization based on user context also taking advantage of a user’s social network. The proposed solution is primarily evaluated in the domain of scientific publications, i.e. digital libraries, with possible extensions to other application domains.


User Model Domain Ontology Information Space User Characteristic Visual Navigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Levene, M., Wheeldon, R.: Navigating the World-Wide-Web. In: Levene, M., Poulovassilis, A. (eds.) Web Dynamics: Adapting to Change in Content, Size, Topology and Use, pp. 117–151. Springer, Heidelberg (2004)Google Scholar
  2. 2.
    Jansen, B.J., Spink, A., Bateman, J., Saracevic, T.: Real life information retrieval: a study of user queries on the web. SIGIR Forum 32(1), 5–17 (1998)CrossRefGoogle Scholar
  3. 3.
    Markkula, M., Sormunen, E.: End-user searching challenges indexing practices in the digital newspaper photo archive. Inf. Retr. 1(4), 259–285 (2000)zbMATHCrossRefGoogle Scholar
  4. 4.
    Yee, K.P., Swearingen, K., Li, K., Hearst, M.: Faceted metadata for image search and browsing. In: CHI 2003. Proc. of the SIGCHI conf. on Human factors in computing systems, pp. 401–408. ACM Press, New York (2003)CrossRefGoogle Scholar
  5. 5.
    Wynar, B.S., Taylor, A.G.: Introduction to Cataloging and Classification. Libraries Unlimited Inc. (1992)Google Scholar
  6. 6.
    Oren, E., Delbru, R., Decker, S.: Extending faceted navigation for rdf data. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 559–572. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Mäkelä, E., Hyvönen, E., Saarela, S., Viljanen, K.: Ontoviews - a tool for creating semantic web portals. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 797–811. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Raitner, M.: Efficient Visual Navigation of Hierarchically Structured Graphs. PhD thesis, University of Passau (2004)Google Scholar
  9. 9.
    Schulz, H.J., Schumann, H.: Visualizing Graphs - A Generalized View. In: IV 2006. 10th International Conference on Information Visualisation, pp. 166–173 (2006)Google Scholar
  10. 10.
    Shadbolt, N., Berners-Lee, T., Hall, W.: The semantic web revisited. IEEE Intelligent Systems 21(3), 96–101 (2006)CrossRefGoogle Scholar
  11. 11.
    Tvarožek, M., Bieliková, M.: Adaptive faceted browser for navigation in open information spaces. In: WWW 2007: Proc. of the 16th Int. Conf. on World Wide Web, pp. 1311–1312. ACM Press, New York (2007)CrossRefGoogle Scholar
  12. 12.
    Tvarožek, M., Bieliková, M.: Personalized faceted navigation for multimedia collections. In: SMAP 2007: Proc. of the 2nd Int. Workshop on Semantic Media Adaptation and Personalization (accepted, 2007)Google Scholar
  13. 13.
    Brusilovsky, P., Rizzo, R.: Map-based horizontal navigation in educational hypertext. In: HYPERTEXT 2002. Proc. of the 13th ACM Conf. on Hypertext and Hypermedia, pp. 1–10. ACM Press, New York (2002)CrossRefGoogle Scholar
  14. 14.
    Bielikova, M., Jemala, M.: Incremental visual browsing of ontology structure based on metadata evaluation and usage. In: HYPERTEXT 2007. Proc. of the 13th ACM Conf. on Hypertext and Hypermedia, ACM Press, New York (2007)Google Scholar
  15. 15.
    Yudelson, M., Brusilovsky, P., Zadorozhny, V.: A User Modeling Server for Contemporary Adaptive Hypermedia: An Evaluation of the Push Approach to Evidence Propagatation. In: Conati, C., McCoy, K., Paliouras, G. (eds.) UM 2007, Corfu, Greece. LNCS (LNAI), vol. 4511, pp. 27–36 (2007)Google Scholar
  16. 16.
    Andrejko, A., Barla, M., Bieliková, M., Tvarožek, M.: User Characteristics Acquisition from Logs with Semantics. In: Kelemenová, A., Kolář, D., Meduna, A., Zendulka, J. (eds.) ISIM 2007. 10th Int. Conf. on Information System Implementation and Modeling, Hradec nad Moravicí, Czech Republic, pp. 103–110 (2007)Google Scholar
  17. 17.
    Barla, M., Bieliková, M.: Estimation of User Characteristics using Rule-based Analysis of User Logs. In: UM 2007. Data Mining for User Modeling, Proc. of Workshop held at the Int. Conf. on User Modeling, Corfu, Greece, pp. 5–14 (2007)Google Scholar
  18. 18.
    Tvarožek, M., Barla, M., Bieliková, M.: Personalized Presentation in Web-Based Information Systems. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds.) SOFSEM 2007. LNCS, vol. 4362, pp. 796–807. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Michal Tvarožek
    • 1
  • Michal Barla
    • 1
  • György Frivolt
    • 1
  • Marek Tomša
    • 1
  • Mária Bieliková
    • 1
  1. 1.Institute of Informatics and Software Engineering, Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

Personalised recommendations