Statistical Methods for Recommender Systems

Statistical Methods for Recommender Systems

;

Cambridge University Press

02/2016

298

Dura

Inglês

9781107036079

540

Descrição não disponível.
Part I. Introduction: 1. Introduction; 2. Classical methods; 3. Explore/exploit for recommender problems; 4. Evaluation methods; Part II. Common Problem Settings: 5. Problem settings and system architecture; 6. Most-popular recommendation; 7. Personalization through feature-based regression; 8. Personalization through factor models; Part III. Advanced Topics: 9. Factorization through latent dirichlet allocation; 10. Context-dependent recommendation; 11. Multi-objective optimization.
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