Making Web Users’ Domain Models Explicit by Applying Ontologies

  • Tarmo Robal
  • Hele-Mai Haav
  • Ahto Kalja
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4802)


When searching the web, users have an implicit conceptual model of the domain in their mind. This model is based on their knowledge of the domain and as a rule does not entirely match to the given web site topology. In this paper, we provide a solution to this mismatching problem by making web users’ domain models explicit by using ontologies created on the basis of the user profile mining on the web. The provided method and system enable to improve web ontologies and existing web site topologies to become closer to the user preferences as well as derive new and specific ones.


Domain ontology modelling Semantic Web Web mining 


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  1. 1.
    Srivastava, J., Cooley, R., Deshpande, M., Tan, P.N.: Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. SIGKDD Explorations 1(2), 12–23 (2000)CrossRefGoogle Scholar
  2. 2.
    Mobasher, B., Cooley, R., Srivastava, J.: Automatic Personalization Based on Web Usage Mining. Communications of the ACM 43(8), 142–151 (2000)CrossRefGoogle Scholar
  3. 3.
    Kolari, P., Joshi, A.: Web Mining - Research and Practice. IEEE Computing in Science and Engineering - Web Engineering Special Issue 6(4), 49–53 (2004)Google Scholar
  4. 4.
    Eirinaki, M., Lampos, C., Paulakis, S., Vazirgiannis, M.: Web Personalization Integrating Content semantics and Navigational Patterns. In: 6th ACM International Workshop on Web Information and Data Management, Washington DC, USA, pp. 72–79. ACM Press, New York (2004)CrossRefGoogle Scholar
  5. 5.
    Middleton, S., De Roure, D., Shadbolt, N.: Capturing Knowledge of User Preferences: Ontologies in Recommender Systems. In: 1st Int. Conference on Knowledge Capture, pp. 100–107. ACM Press, New York (2001)CrossRefGoogle Scholar
  6. 6.
    Hartmann, J., Sure, Y.: An Infrastructure for Scalable, Reliable Semantic Portals. IEEE Intelligent Systems 19(3), 58–65 (2004)CrossRefGoogle Scholar
  7. 7.
    Jin, Y., Decker, S., Wiederhold, G.: OntoWebber: Model-Driven Ontology-Based Web Site Management. In: SWWS 2001. 1st Int. Semantic Web Working Symp., pp. 529–547 (2001)Google Scholar
  8. 8.
    OWL Web Ontology Language,
  9. 9.
  10. 10.
    The Protégé Ontology Editor and Knowledge Acquisition System,
  11. 11.
    Robal, T., Kalja, A.: Applying User Profile Ontology for Mining Web Site Adaptation Recommendations. In: ADBIS 2007. 11th East-European Conference on Advances in Databases and Information Systems, Varna, Bulgaria (accepted paper, 2007)Google Scholar
  12. 12.
    Kosala, R., Blockeel, H.: Web Mining Research: A Survey. ACM SIGKDD Explorations 2(1), 1–15 (2000)CrossRefGoogle Scholar
  13. 13.
    Li, Y., Zhong, N.: Mining Ontology for Automatically Acquiring Web User Information Needs. IEEE Transactions on Knowledge and Data Engineering 18(4), 554–568 (2006)CrossRefMathSciNetGoogle Scholar
  14. 14.
    Davison, B.: Web Traffic Logs: An Imperfect Resource for Evaluation. In: INET 1999. Proceedings of Ninth Annual Conference of the Internet Society, San Jose, CA (1999)Google Scholar
  15. 15.
    Robal, T., Kalja, A., Põld, J.: Analysing the Web Log to Determine the Efficiency of Web Systems. In: DB&IS 2006. Proc. of the 7th International Baltic Conference on Databases and Information Systems, Technika, Lithuania, pp. 264–275 (2006)Google Scholar
  16. 16.
    Kimball, R., Margy, R.: The data warehouse toolkit: the complete guide to dimensional modelling. John Wiley & Sons, England (2002)Google Scholar
  17. 17.
  18. 18.
    Berendt, B., Hotho, A., Mladenic, D., Someren, M., Spiliopoulou, M., Stumme, G.: A Roadmap for Web Mining: From Web to Semantic Web. In: Berendt, B., Hotho, A., Mladenić, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds.) EWMF 2003. LNCS (LNAI), vol. 3209, pp. 1–22. Springer, Heidelberg (2004)Google Scholar
  19. 19.
    Baglioni, M., Ferrara, U., Romei, A., Ruggieri, S., Turini, F.: Preprocessing and Mining Web Log Data for Web personalization. In: Cappelli, A., Turini, F. (eds.) AI*IA 2003: Advances in Artificial Intelligence. LNCS, vol. 2829, pp. 237–249. Springer, Heidelberg (2003)Google Scholar
  20. 20.
    Lim, E-P., Sun, A.: Web Mining – the Ontology Approach. In: Int. Advanced Digital Library Conference (IADLC 2005), Nagoya University, Nagoya, Japan (2005),
  21. 21.
    Mikroyannidis, A., Theodoulidis, B.: Web usage Driven Adaptation of the Semantic Web. In: Proceedings of UserSWeb: Workshop on End User Aspects of the Semantic Web, Heraklion, Crete, pp. 137–147 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Tarmo Robal
    • 1
  • Hele-Mai Haav
    • 2
  • Ahto Kalja
    • 1
    • 2
  1. 1.Dept. of Computer Engineering, Tallinn University of Technology, Raja 15, 12618 TallinnEstonia
  2. 2.Institute of Cybernetics at Tallinn University of Technology, Akadeemia 21, 12618 TallinnEstonia

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