A Recommender System based on the Immune Network

Tools

Cayzer, Steve and Aickelin, Uwe (2002) A Recommender System based on the Immune Network. In: CEC 2002, 2002, Honolulu, USA.

This is the latest version of this item.

Full text not available from this repository.

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.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/1022738
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 12 Oct 2007 15:30
Last Modified: 04 May 2020 20:32
URI: https://eprints.nottingham.ac.uk/id/eprint/635

Available Versions of this Item

Actions (Archive Staff Only)

Edit View Edit View