By Panagiotis Symeonidis,Andreas Zioupos
This ebook provides the algorithms used to supply thoughts via exploiting matrix factorization and tensor decomposition strategies. It highlights recognized decomposition tools for recommender structures, akin to Singular price Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), and so on. and describes intimately the professionals and cons of every approach for matrices and tensors. This publication presents a close theoretical mathematical heritage of matrix/tensor factorization options and a step by step research of every strategy at the foundation of an built-in toy instance that runs all through all its chapters and is helping the reader to appreciate the most important adjustments between equipment. It additionally comprises chapters, the place diverse matrix and tensor equipment are in comparison experimentally on actual information units, resembling Epinions, GeoSocialRec, Last.fm, BibSonomy, and so forth. and gives additional insights into the benefits and downsides of every process.
The publication deals a wealthy mix of thought and perform, making it appropriate for college kids, researchers and practitioners drawn to either recommenders and factorization tools. academics may also use it for sessions on information mining, recommender platforms and dimensionality relief methods.
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Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science) by Panagiotis Symeonidis,Andreas Zioupos