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...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2016, 2016
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| Edition: | 1st ed. 2016 |
| Series: | SpringerBriefs in Computer Science
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
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