Machine Learning Paradigms Applications in Recommender Systems /

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perfo...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Lampropoulos, Aristomenis S. (Autor), Tsihrintzis, George A. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Intelligent Systems Reference Library, 92
Temas:
Computational intelligence.
Artificial intelligence.
Image processing-Digital techniques.
Computer vision.
Computational Intelligence.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • Review of Previous Work Related to Recommender Systems
  • The Learning Problem.-Content Description of Multimedia Data
  • Similarity Measures for Recommendations based on Objective Feature Subset Selection
  • Cascade Recommendation Methods
  • Evaluation of Cascade Recommendation Methods
  • Conclusions and Future Work.

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