Advertisement

Immune-Inspired Adaptive Information Filtering

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

Abstract

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.

Keywords

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Menczer, F.: ARACHNID: Adaptive retrieval agents choosing heuristic neighborhoods for information discovery. In: 14th International Machine Learning Conference, pp. 227–235 (1997)Google Scholar
  2. 2.
    Gaspar, A., Collard, P.: From GAs to artificial immune systems: Improving adaptation in time dependent optimization. In: Proceedings of the Congress on Evolutionary Computation, vol. 3, pp. 1859–1866. IEEE Press, Los Alamitos (1999)Google Scholar
  3. 3.
    Simoens, A., Costa, E.: An immune system-based genetic algorithm to deal with dynamic environments: Diversity and memory. In: Sixth International Conference on Neural Networks and Genetic Algorithms, pp. 168–174. Springer, Heidelberg (2003)Google Scholar
  4. 4.
    Nanas, N., Uren, V., de Roeck, A., Domingue, J.: Multi-topic information filtering with a single user profile. In: 3rd Hellenic Conference on Artificial Intelligence, pp. 400–409 (2004)Google Scholar
  5. 5.
    Nanas, N., Uren, V., de Roeck, A.: Nootropia: a user profiling model based on a self-organising term network. In: 3rd International Conference on Artificial Immune Systems, pp. 146–160 (2004)Google Scholar
  6. 6.
    Sheth, B.D.: A Learning Approach to Personalized Information Filtering. Master of Science, Massachusetts Institute of Technology (1994)Google Scholar
  7. 7.
    Winiwarter, W.: PEA - a personal email assistant with evolutionary adaptation. International Journal of Information Technology 5(1) (1999)Google Scholar
  8. 8.
    Moukas, A., Maes, P.: Amalthaea: An evolving multi-agent information filtering and discovery system for the WWW. In: Autonomous Agents and Multi-Agent Systems, pp. 59–88 (1998)Google Scholar
  9. 9.
    Menczer, F., Monge, A.E.: Scalable web search by adaptive online agents: An infospiders case study. In: Klusch, M. (ed.) Intelligent Information Agents: Agent-Based Information Discovery and Management on the Internet, pp. 323–347. Springer, Heidelberg (1999)Google Scholar
  10. 10.
    Dasgupta, D. (ed.): Artificial Immune Systems and Their Applications. Springer, Heidelberg (1998)Google Scholar
  11. 11.
    Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, Heidelberg (2002)zbMATHGoogle Scholar
  12. 12.
    Tarakanov, A.O., Skormin, V.A., Sokolova, S.P.: Immunocomputing: Principles and Applications. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  13. 13.
    Farmer, J.D., Packard, N.H., Perelson, A.S.: The immune system, adaptation, and machine learning. Physica 22D, 187–204 (1986)MathSciNetGoogle Scholar
  14. 14.
    Chao, D.L., Forrest, S.: Information immune systems. Genetic Programming and Evolvable Machines 4, 311–331 (2003)CrossRefGoogle Scholar
  15. 15.
    Twycross, J., Cayzer, S.: An immune-based approach to document classification. Technical Report HPL-2002-292, HP Research Bristol (2002)Google Scholar
  16. 16.
    Secker, A., Freitas, A.A., Timmis, J.: Aisec: an artificial immune system for e-mail classification. In: Congress on Evolutionary Computation, pp. 131–139. IEEE, Los Alamitos (2003)Google Scholar
  17. 17.
    Oda, T., White, T.: Immunity from spam: An analysis of an artificial immune system for junk email detection. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 276–289. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Maturana, H.R., Varela, F.J.: Autopoiesis and Cognition. Dordrecht, Holland (1980)Google Scholar
  19. 19.
    Varela, F.J., Coutinho, A.: Second generation immune network. Immunology Today 12, 159–166 (1991)Google Scholar
  20. 20.
    Bersini, H., Varela, F.: The immune learning mechanisms: Reinforcement, recruitment and their applications. In: Computing with Biological Metaphors, pp. 166–192. Chapman Hall, Boca Raton (1994)Google Scholar
  21. 21.
    Neal, M.: Meta-stable memory in an artificial immune network. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 168–180. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  22. 22.
    Mohr, P.H., Ryan, N., Timmis, J.: Exploiting immunological properties for ubiquitous computing systems. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds.) ICARIS 2004. LNCS, vol. 3239, pp. 277–289. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  23. 23.
    Widyantoro, D.H., Loerger, T.R., Yen, J.: Learning user interests dynamics with a three-descriptor representation. JASIS 52(3), 212–225 (2000)CrossRefGoogle Scholar
  24. 24.
    Robertson, S., Soboroff, I.: The TREC 2001 filtering track report. In: TREC-10 (2001)Google Scholar

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.

Personalised recommendations