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Particle swarm optimization recommender system

Ujjin, S; Bentley, PJ; (2003) Particle swarm optimization recommender system. In: (Proceedings) IEEE Swarm Intelligence Symposium. (pp. pp. 124-131). IEEE

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Recommender systems are new types of internet-based software tools, designed to help users rind their way through today's complex on-line shops and entertainment websites. This paper describes a new recommender system, which employs a particle swarm optimization (PSO) algorithm to learn personal preferences of users and provide tailored suggestions. Experiments are carried out to observe the performance of the system and results are compared to those obtained from the genetic algorithm (GA) recommender system I I I and a standard, non-adaptive system based on the Pearson algorithm [2].

Type: Proceedings paper
Title: Particle swarm optimization recommender system
Event: IEEE Swarm Intelligence Symposium
Dates: 24 April 2003 - 26 April 2003
ISBN: 0-7803-7914-4
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/171645
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