Matrix and Tensor Factorization Techniques for Recommender Systems

This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factoriz...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Symeonidis, Panagiotis (Author), Zioupos, Andreas (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:SpringerBriefs in Computer Science,
Subjects:
Information storage and retrieval systems.
Computer science-Mathematics.
Artificial intelligence.
Information Storage and Retrieval.
Mathematical Applications in Computer Science.
Mathematics of Computing.
Artificial Intelligence.
Online Access:Texto Completo
Table of Contents:
  • Part I Matrix Factorization Techniques
  • 1. Introduction
  • 2. Related Work on Matrix Factorization
  • 3. Performing SVD on matrices and its Extensions
  • 4. Experimental Evaluation on Matrix Decomposition Methods
  • Part II Tensor Factorization Techniques
  • 5. Related Work on Tensor Factorization
  • 6. HOSVD on Tensors and its Extensions
  • 7. Experimental Evaluation on Tensor Decomposition Methods
  • 8 Conclusions and Future Work.

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