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A Recommender System based on the Immune Network

Cayzer, Steve; Aickelin, Uwe

Authors

Steve Cayzer

Uwe Aickelin



Abstract

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Citation

Cayzer, S., & Aickelin, U. (2002). A Recommender System based on the Immune Network.

Conference Name CEC 2002
Publication Date Jan 1, 2002
Deposit Date Oct 12, 2007
Publicly Available Date Oct 12, 2007
Peer Reviewed Peer Reviewed
Public URL https://nottingham-repository.worktribe.com/output/1022738

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