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Natural Computing

Erschienen in:

01.06.2009

Autopoiesis, the immune system, and adaptive information filtering

verfasst von: Nikolaos Nanas, Anne de Roeck

Erschienen in: Natural Computing | Ausgabe 2/2009

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Abstract

Adaptive information filtering is a challenging and fascinating problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We tackle this dynamic problem with Nootropia, a model inspired by the autopoietic view of the immune system. It is based on a self-organising antibody network that reacts to user feedback in order to define and preserve the user interests. We describe Nootropia in the context of adaptive, content-based document filtering and evaluate it using virtual users. The results demonstrate Nootropia’s ability to adapt to both short-term variations and more radical changes in the user’s interests, and to dynamically control its size and connectivity in the process. Advantages over existing approaches to profile adaptation, such as learning algorithms and evolutionary algorithms are also highlighted.

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A similar model is described in Bersini (2002).

No distinction between B-cell and antibody concentrations is made.

In the case of binary document indexing, considered for our experiments, each activated term receives an initial activation equal to one. More generally, a term’s initial activation can be set equal to the term’s weight in document D.

E.g., inferred based on reading times, eye ball tracking and other evidence.

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This number has been increased from 1000 as in the TREC guidelines, to 3000 as an additional remedy to problems deriving from the large number of relevant documents per topic in RCV1 (Robertson and Soboroff 2001).

A more comprehensive presentation and analysis of the results can be found in Nanas (2003).

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Titel: Autopoiesis, the immune system, and adaptive information filtering
verfasst von: Nikolaos Nanas
Anne de Roeck
Publikationsdatum: 01.06.2009
Verlag: Springer Netherlands
Erschienen in: Natural Computing / Ausgabe 2/2009
Print ISSN: 1567-7818
Elektronische ISSN: 1572-9796
DOI: https://doi.org/10.1007/s11047-008-9068-x

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