Particle swarm optimization recommender system

@inproceedings{Ujjin2003ParticleSO,
  title={Particle swarm optimization recommender system},
  author={Supiya Ujjin and Peter J. Bentley},
  booktitle={SIS},
  year={2003}
}
Recommender systems are new types of internet-based software tools, designed to help users find 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… CONTINUE READING
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A Recommender System based on the Immune Network

ArXiv • 2002
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Learning User Preferences Using Evolution

S. Ujjin, P. J. Bentley
In Proceedings of the 4 Asia-Pacific Conference on Simulated Evolution and Learning. Singapore • 2002
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January

J. B. Schafer, J. A. Konstan, J. Riedl
2001

Particle Swarm Optimization: Developments, Applications and Resources

R. C. Eberhart, Y. Shi
In Proceedings of the 2001 Congress on Evolutionary Computation • 2001
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