Learning Interaction Models in a Digital Library Service

  • Giovanni Semeraro
  • Stefano Ferilli
  • Nicola Fanizzi
  • Fabio Abbattista
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)


We present the exploitation of an improved version of the Learning Server for modeling the user interaction in a digital library service architecture. This module is the basic component for providing the service with an added value such as an essential extensible form of interface adaptivity. Indeed, the system is equipped with a web-based visual environment, primarily intended to improve the user interaction by automating the assignment of a suitable interface depending on data relative to the previous experience with the system, coded in log files. The experiments performed show that accurate interaction models can be inferred automatically by using up-to-date learning algorithms.


Digital Library Classification Rule User Class User Classification Interface Adaptivity 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Giovanni Semeraro
    • 1
  • Stefano Ferilli
    • 1
  • Nicola Fanizzi
    • 1
  • Fabio Abbattista
    • 1
  1. 1.Dipartimento di InformaticaUniversità di BariBariItaly

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