By Panagiotis Symeonidis,Andreas Zioupos
This booklet provides the algorithms used to supply ideas through exploiting matrix factorization and tensor decomposition ideas. It highlights famous decomposition tools for recommender platforms, resembling Singular price Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), and so forth. and describes intimately the professionals and cons of every strategy for matrices and tensors. This publication presents a close theoretical mathematical history of matrix/tensor factorization strategies and a step by step research of every approach at the foundation of an built-in toy instance that runs all through all its chapters and is helping the reader to appreciate the foremost alterations between tools. It additionally includes chapters, the place assorted matrix and tensor equipment are in comparison experimentally on actual info units, equivalent to Epinions, GeoSocialRec, Last.fm, BibSonomy, and so on. and gives additional insights into the benefits and drawbacks of every approach.
The publication deals a wealthy combination of concept and perform, making it compatible for college kids, researchers and practitioners drawn to either recommenders and factorization equipment. teachers may also use it for sessions on info mining, recommender platforms and dimensionality aid methods.
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Matrix and Tensor Factorization Techniques for Recommender Systems (SpringerBriefs in Computer Science) by Panagiotis Symeonidis,Andreas Zioupos
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