Da: Chiron Media, Wallingford, Regno Unito
EUR 67,60
Convertire valutaQuantità: 10 disponibili
Aggiungi al carrelloPF. Condizione: New.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 82,71
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 73,40
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: California Books, Miami, FL, U.S.A.
EUR 94,45
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Aggiungi al carrelloCondizione: New.
Da: Books Puddle, New York, NY, U.S.A.
EUR 107,51
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. pp. 108.
Da: Russell Books, Victoria, BC, Canada
EUR 105,21
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Aggiungi al carrelloPaperback. Condizione: New. 1st ed. 2016. Special order direct from the distributor.
Editore: Springer, Berlin, Springer International Publishing, Springer, 2017
ISBN 10: 3319413562 ISBN 13: 9783319413563
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 83,47
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.
Editore: Springer International Publishing, 2017
ISBN 10: 3319413562 ISBN 13: 9783319413563
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 70,87
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Editore: Springer-Verlag New York Inc, 2017
ISBN 10: 3319413562 ISBN 13: 9783319413563
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 119,75
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 108 pages. 9.00x6.00x0.25 inches. In Stock.
Da: dsmbooks, Liverpool, Regno Unito
EUR 127,16
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. New. book.
Editore: Springer, Berlin, Springer International Publishing, Springer, 2017
ISBN 10: 3319413562 ISBN 13: 9783319413563
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 80,24
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods. 102 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 111,65
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. 108.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 113,45
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 108.