Immune-Inspired Adaptive Information Filtering

  • Nikolaos Nanas
  • Anne de Roeck
  • Victoria Uren
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4163)


Adaptive information filtering is a challenging research problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We investigate the application of an immune-inspired approach to this problem. Nootropia, is a user profiling model that has many properties in common with computational models of the immune system that have been based on Franscisco Varela’s work. In this paper we concentrate on Nootropia’s evaluation. We define an evaluation methodology that uses virtual user’s to simulate various interest changes. The results show that Nootropia exhibits the desirable adaptive behaviour.


Evaluation Methodology User Interest Immune Network Training Document Information Filter 
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 2006

Authors and Affiliations

  • Nikolaos Nanas
    • 1
  • Anne de Roeck
    • 1
  • Victoria Uren
    • 2
  1. 1.Computing DepartmentThe Open UniversityMilton KeynesU.K.
  2. 2.Knowledge Media InstituteThe Open UniversityMilton KeynesU.K.

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