Semantic Web Technologies for the Adaptive Web

  • Peter Dolog
  • Wolfgang Nejdl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4321)

Abstract

Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web.

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References

  1. 1.
    Agosti, M., Crestani, F., Melucci, M.: Design and implementation of a tool for the automatic construction of hypertexts for information retrieval. Inf. Process. Manage 32(4), 459–476 (1996)CrossRefGoogle Scholar
  2. 2.
    Brickley, D., Guha, R.V.: Resource Description Framework (RDF) Schema Specification 1 (2002), http://www.w3.org/TR/rdf-schema
  3. 3.
    Brusilovsky, P.: Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction 6(2-3), 87–129 (1996)CrossRefGoogle Scholar
  4. 4.
    Brusilovsky, P.: Adaptive navigation support. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 263–290. Springer, Heidelberg (2007)Google Scholar
  5. 5.
    Brusilovsky, P., Maybury, M.T.: From adaptive hypermedia to the adaptive web. Commun. ACM 45(5), 30–33 (2002)CrossRefGoogle Scholar
  6. 6.
    Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 3–53. Springer, Heidelberg (2007)Google Scholar
  7. 7.
    Brusilovsky, P., Nejdl, W.: Adaptive hypermedia and adaptive web. In: Singh, M. (ed.) Practical Handbook of Internet Computing, pp. 1–12. CRC Press (2004)Google Scholar
  8. 8.
    Bruza, P.D.: Hyperindices: a novel aid for searching in hypermedia, pp. 109–122 (1992)Google Scholar
  9. 9.
  10. 10.
    Denaux, R., Dimitrova, V., Aroyo, L.: Integrating open user modeling and learning content management for the semantic web. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 9–18. Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Dolog, P., Henze, N., Nejdl, W., Sintek, M.: The personal reader: Personalizing and enriching learning resource using semantic web technologies. In: De Bra, P., Nejdl, W. (eds.) AH 2004. LNCS, vol. 3137, pp. 85–94. Springer, Heidelberg (2004)Google Scholar
  12. 12.
    Dolog, P., Henze, N., Nejdl, W., Sintek, M.: Personalization in distributed e-learning environments. In: Proc. of WWW2004 — The Thirteen International World Wide Web Conference, pp. 170–179. ACM Press, New York (May 2004)Google Scholar
  13. 13.
    Dolog, P., Schäfer, M.: A framework for browsing, manipulating and maintaining interoperable learner profiles. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 397–401. Springer, Heidelberg (2005)Google Scholar
  14. 14.
    Domingue, J., Dzbor, M.: Magpie: supporting browsing and navigation on the semantic web. In: Vanderdonckt, J., Nunes, N.J., Rich, C. (eds.) Proceedings of the 2004 International Conference on Intelligent User Interfaces, Funchal, Madeira, Portugal, pp. 191–197. ACM Press, New York (Jan. 2004)CrossRefGoogle Scholar
  15. 15.
    S.Q.L. for RDF: Sparql query language for rdf (2006), published online at http://www.w3.org/TR/rdf-sparql-query/.
  16. 16.
    Goble, C., Bechhofer, S., Carr, L., Roure, D.D., Hall, W.: Conceptual open hypermedia = the semantic web. In: Decker, S., Fensel, D., Sheth, A., Staab, S. (eds.) Proceedings of the SemWeb2001, The Second International Workshop on the Semantic Web at World Wide Web Conference — WWW10, Hong Kong (May 2001), Available at: http://CEUR-WS.org/Vol-40/Goble-et-al.pdf
  17. 17.
    Grønbæk, K., Trigg, R.H.: Design issues for a dexter-based hypermedia system. Commun. ACM 37(2), 40–49 (1994)CrossRefGoogle Scholar
  18. 18.
    Hall, W.: Ending the tyranny of the button. IEEE MultiMedia 1(1), 60–68 (1994)CrossRefGoogle Scholar
  19. 19.
    Henze, N., Dolog, P., Nejdl, W.: Towards personalized e-learning in a semantic web. Educational Technology and Society Journal 7(4) Special Issue on Ontologies and the Semantic Web for E-learning, 82–97 (2004)Google Scholar
  20. 20.
    IEEE: IEEE P1484.2/D7, 2000-11-28. draft standard for learning technology. public and private information (papi) for learners (papi learner) (2000), available at: http://ltsc.ieee.org/archive/harvested-2003-10/working_groups/wg2.zip Accessed on December 20, 2003
  21. 21.
    IMS: IMS learner information package specification. Available at: http://www.imsproject.org/profiles/index.cfm Accessed on October 25, 2002
  22. 22.
    Kifer, M., Lausen, G., Wu, J.: Logical foundations of object-oriented and frame-based languages. J. ACM 42(4), 741–843 (1995)MATHCrossRefMathSciNetGoogle Scholar
  23. 23.
    Lassila, O., Swick, R.: W3C resource description framework (rdf) model and syntax specification. Available at: http://www.w3.org/TR/REC-rdfsyntax/ (Accessed on October 25, 2002)
  24. 24.
    Micarelli, A., Sciarrone, F., Marinilli, M.: Web document modeling. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 155–194. Springer, Heidelberg (2007)Google Scholar
  25. 25.
    Millard, D.E., Moreau, L., Davis, H.C., Reich, S.: FOHM: a fundamental open hypertext model for investigating interoperability between hypertext domains. In: Proceedings of the eleventh ACM on Hypertext and hypermedia, pp. 93–102. ACM Press, New York (2000)CrossRefGoogle Scholar
  26. 26.
    Nanard, J., Nanard, M.: Using structured types to incorporate knowledge in hypertext. In: HYPERTEXT ’91: Proceedings of the third annual ACM conference on Hypertext, pp. 329–343. ACM Press, New York (1991)CrossRefGoogle Scholar
  27. 27.
    Nejdl, W., Wolf, B., Qu, C., Decker, S., Sintek, M., Naeve, A., Nilsson, M., Palmér, M., Risch, T.: EDUTELLA: a P2P Networking Infrastructure based on RDF. In: Proc. of 11th World Wide Web Conference, Hawaii, USA, May 2002, pp. 604–615. ACM Press, New York (2002)Google Scholar
  28. 28.
    Nilsson, M., Siberski, W.: RDF Query Exchange Language (QEL) - Concepts, Semantics and RDF Syntax. Available at: http://edutella.jxta.org/spec/qel.html Accessed 20th September, 2003
  29. 29.
    Nürnberg, P.J., Leggett, J.J., Wiil, U.K.: An agenda for open hypermedia research. In: Proceedings of the Ninth ACM Conference on Hypertext and Hypermedia: Links, Objects, Time and Space - Structure in Hypermedia Systems. HYPERTEXT ’98, Pittsburgh, PA, USA, June 1998, pp. 198–206. ACM Press, New York (1998)CrossRefGoogle Scholar
  30. 30.
    A of Computing machinery. The acm computer classification system (2002), http://www.acm.org/class/1998/
  31. 31.
    Pazzani, M.J., Billsus, D.: Content-based recommendation systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)Google Scholar
  32. 32.
    Sintek, M., Decker, S.: TRIPLE—A query, inference, and transformation language for the semantic web. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 364–378. Springer, Heidelberg (2002)Google Scholar
  33. 33.
    Tudhope, D., Taylor, C.: Navigation via similarity: automatic linking based on semantic closeness. Inf. Process. Manage 33(2), 233–242 (1997)CrossRefGoogle Scholar
  34. 34.
    W3C: Owl web ontology language semantics and abstract syntax. Technical Report (August 2003), Available at: http://www.w3.org/TR/owl-semantics/ Accessed: 20th September 2003
  35. 35.
    Weiss, R., Vélez, B., Sheldon, M.A., Namprempre, C., Szilagyi, P., Duda, A., Gifford, D.K.: Hypursuit: A hierarchical network search engine that exploits content-link hypertext clustering. In: Hypertext ’96, The Seventh ACM Conference on Hypertext, Washington DC, USA, March 1996, pp. 180–193. ACM Press, New York (1996)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Peter Dolog
    • 1
  • Wolfgang Nejdl
    • 2
  1. 1.Department of Computer Science, Aalborg University, Fredrik Bajers Vej 7E, DK-9220 AalborgDenmark
  2. 2.L3S Research Center, University of Hannover, Appelstrasse 9A, 30167 HannoverGermany

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