Floriana Esposito, Oriana Licchelli, Pasquale Lops, Giovanni Semeraro


E-Learning Systems enable students to work with electronic teaching materials, to join online courses, to pass tests, and to communicate with other students or instructors. An important requirement of this systems is the integration of external knowledge management resources into them. The digital libraries are helpful to this purpose because materials of many digital libraries are valuable for learning. The availability of teaching materials provided by an E-Learning Systems can be enlarged by reverting to materials existing in several digital libraries. In this case, it is necessary to find the right document source and to supply the suitable documents basing on the student requirements, also when the student model of the e-learning system is still not available. In this paper, we have focused our attention on the use of user profiles, generated by a personalization system (the Profile Extractor), to improve searching among digital libraries or other generic information sources.


  1. Balabanovic, M. and Shoham, Y., 1997. Fab: ContentBased, Collaborative recommendation. Communications of ACM, 40 (3),66-72.
  2. Billsus, D. and Pazzani, M. J., 1998. Learning Collaborative Information Filters. In Proceedings of the International Conference on Machine Learning, Wisconsin, USA, 46-54.
  3. Brusilovsky, P., 1996. Methods and techniques in adaptive hypermedia. User Modelling and User-Adapted Interaction, 6(2-3), 87-129.
  4. Bordoni, L., 2002. COVAX: A Contemporary Culture Virtual Archive in XML. In Proceedings of the 6th European Conference ECDL 2002, Rome, Italy, 661- 662.
  5. Bull, S., Brna, P, and Pain, H., 1995. Extending the scope of the student model. User Modelling and UserAdapted Interaction, 5(10), 45-65.
  6. Bull, S. and Smith, M., 1997. A pair of student models to encourage collaboration. In Proceedings of the 6th International Conference on User Modeling UM97, Italia, 339-341.
  7. Cummings, G., 1998. Artificial intelligence in education: an exploration. Journal of Computer Assisted Learning, 14(4) 252-259.
  8. Hammond, K. J., Burke, R. and Schmitt, K., 1996. A Case-Based Approach to Knowledge Navigation. Case-Based Reasoning Experiences Lessons and Future Directions, MIT Press, 125-136.
  9. Hartley, J.R., 1998. Ospite Editoriale: CAL and AI - a time for rapprochement? Journal of Computer Assisted Learning, 14(4), 249-250.
  10. Jennings, A. and Higuchi, H., 1993. A user model neural network for a personal news service. User Modeling and User-Adapted Information, 3(1), 1-25.
  11. Konstan, J. A., Miller, B. N., Maltz, D., Herlochker, J. L., Gordan, L. R. and Riedl, J., 1997. Grouplens: Applying Collaborative Filtering to Usenet News. Communications of the ACM, 40(3), 77-87.
  12. Lauzon, A.C. and Moore, G.A.B., 1989. A fourth generation distance education system: Integrating computer-assisted learning and computer conferencing. The American Journal of Distance Education, 3(1), 38-49.
  13. Maish Nichani. LCMS = LMS + CMS 2.asp
  14. Ohlsson, S., 1993. Impact of cognitive theory on the practice of authoring. Journal of Computer Assisted Learning, 9(4) 194-221.
  15. Perkowitz, M. and Etzioni, O., 1997. Adaptive Web Sites: An AI Challenge. In Proceedings of the 15th International Joint Conference on Artificial Intelligence, Nagoya, Japan. Morgan Kaufmann, 16- 23.
  16. Ragnemalm, E.L., 1996. Student Diagnosis in Practice; Bridging a Gap. User Modelling and User-Adapted Interaction, 5, 93-116.
  17. Resnick, P. and Varian, H., 1997. Recommender Systems. Communications of the ACM, 40(3), 56-58.
  18. Riecken, D., 2000. Personalized Views of Personalization. Communications of the ACM, 43(8), 27-28.
  19. Rosenberg, M.J., 2001. e-Learning - Strategies for Delivering Knowledge in the Digital Age. McGrawHill.
  20. Self, J.A., 1990. Bypassing the intractable problem of student modelling. Intelligent tutoring systems: at the crossroads of artificial intelligence and education. Frasson, C., Gauthier, G. (eds.), Ablex Publishing, Norwood, New Jersey, 107-123.
  21. Smith, C. and Jagodzinski, P., 1995. The implementation of a multimedia learning environment for graduate civil engineers. Association for Learning Technology Journal, 3(1) 29-39.
  22. Vassileva, J., 1996. A task-centred approach for user modelling in a hypermedia office documentation system. User Modelling and User-Adapted Interaction, 6(2-3) 185-223.
  23. Woolf, B., 1992. AI in Education. Encyclopedia of Artificial Intelligence. Shapiro, S. ed., John Wiley & Sons, Inc., New York, 434-444.

Paper Citation

in Harvard Style

Esposito F., Licchelli O., Lops P. and Semeraro G. (2004). PERSONALIZING DIGITAL LIBRARIES FOR EDUCATION . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: WSMAI, (ICEIS 2004) ISBN 972-8865-00-7, pages 279-284. DOI: 10.5220/0002666602790284

in Bibtex Style

author={Floriana Esposito and Oriana Licchelli and Pasquale Lops and Giovanni Semeraro},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: WSMAI, (ICEIS 2004)},

in EndNote Style

JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: WSMAI, (ICEIS 2004)
SN - 972-8865-00-7
AU - Esposito F.
AU - Licchelli O.
AU - Lops P.
AU - Semeraro G.
PY - 2004
SP - 279
EP - 284
DO - 10.5220/0002666602790284