Improving collaborative filtering recommender system results and performance using genetic algorithms

@article{Bobadilla2011ImprovingCF,
  title={Improving collaborative filtering recommender system results and performance using genetic algorithms},
  author={Jes{\'u}s Bobadilla and Fernando Ortega and Antonio Hernando and Javier Alcal{\'a}},
  journal={Knowl.-Based Syst.},
  year={2011},
  volume={24},
  pages={1310-1316}
}
This paper presents a metric to measure similarity between users, which is applicable in collaborative filtering processes carried out in recommender systems. The proposed metric is formulated via a simple linear combination of values and weights. Values are calculated for each pair of users between which the similarity is obtained, whilst weights are only calculated once, making use of a prior stage in which a genetic algorithm extracts weightings from the recommender system which depend on… CONTINUE READING
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