Web personalized Recommender System for e-business - Couverture souple

Shinde, Subhash K.; Kulkarni, Uday V.

9783659877759: Web personalized Recommender System for e-business

Couverture souple

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Editeur : LAP LAMBERT Academic Publishing, 2018

Afficher les exemplaires de cette �dition comportant l?ISBN

0 D'occasion

6 Neuf

De EUR 55,90

D�tails de l'�dition

�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2018
Langue: anglais
ISBN 10: 3659877751
ISBN 13: 9783659877759
Reliure: Broch�
Nombre de pages: 140
Coordonn�es du fabricant: non disponible
Personne responsable: KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne

R�sultats de recherche pour Web personalized Recommender System for e-business

Image fournie par le vendeur

Web personalized Recommender System for e-business

Subhash K. Shinde

Edit� par LAP LAMBERT Academic Publishing Mrz 2018, 2018

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is to propose an adaptive recommendation model with learning algorithms, which increases web user satisfaction and save on thecosts of content management with minimal human intervention. This researchwork explores a unified model for hybrid filtering with learning algorithms which extracts customer's current browsing patterns and forms group of customersusing different clustering algorithms to obtain implicit users rating forrecommended product. In this research following three novel recommender systems are proposed. These systems are used to investigate issues and challenges related to recommendersystems. Hybrid web personalized recommender system based on web usagemining (HWPRS). Hybrid web personalized recommender system using centeringbunchingbased clustering (CBBCHPRS). Hybrid Fuzzy personalized recommender system using Modified Fuzzyc-means clustering (MFCMHFRS). 140 pp. Englisch. N� de r�f. du vendeur 9783659877759

Contacter le vendeur

Acheter neuf

EUR 55,90

Exp�dition �EUR 23
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Web personalized Recommender System for e-business

Subhash K. Shinde|Uday V. Kulkarni

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Neuf Couverture souple

impression � la demande

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shinde Subhash K.Dr. Subhash K. Shinde is a Professor at Lokmanya Tilak College of Engineering, Navi Mumbai. He completed his Ph.D. ( Computer Engineering) in October 2012 from SRTM,Nanded, India. He is Chairman, B.O.S. in Computer . N� de r�f. du vendeur 385770109

Contacter le vendeur

Acheter neuf

EUR 46,18

Exp�dition �EUR 48,99
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image d'archives

Web personalized Recommender System for e-business

Shinde, Subhash K./ Kulkarni, Uday V.

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Neuf Paperback

Vendeur : Revaluation Books, Exeter, Royaume-Uni

�valuation du vendeur 5 sur 5 �toiles

Paperback. Etat : Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. N� de r�f. du vendeur 3659877751

Contacter le vendeur

Acheter neuf

EUR 102,77

Exp�dition �EUR 11,47
Exp�dition depuis Royaume-Uni vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Web personalized Recommender System for e-business

Subhash K. Shinde

Edit� par LAP LAMBERT Academic Publishing M�r 2018, 2018

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Neuf Taschenbuch

impression � la demande

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is to propose an adaptive recommendation model with learning algorithms, which increases web user satisfaction and save on thecosts of content management with minimal human intervention. This researchwork explores a unified model for hybrid filtering with learning algorithms which extracts customer's current browsing patterns and forms group of customersusing different clustering algorithms to obtain implicit users rating forrecommended product. In this research following three novel recommender systems are proposed. These systems are used to investigate issues and challenges related to recommendersystems. � Hybrid web personalized recommender system based on web usagemining (HWPRS). � Hybrid web personalized recommender system using centeringbunchingbased clustering (CBBCHPRS). � Hybrid Fuzzy personalized recommender system using Modified Fuzzyc-means clustering (MFCMHFRS).VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 140 pp. Englisch. N� de r�f. du vendeur 9783659877759

Contacter le vendeur

Acheter neuf

EUR 55,90

Exp�dition �EUR 60
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Web personalized Recommender System for e-business

Subhash K. Shinde

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 3659877751 ISBN 13 : 9783659877759

Neuf Taschenbuch

impression � la demande

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is to propose an adaptive recommendation model with learning algorithms, which increases web user satisfaction and save on thecosts of content management with minimal human intervention. This researchwork explores a unified model for hybrid filtering with learning algorithms which extracts customer's current browsing patterns and forms group of customersusing different clustering algorithms to obtain implicit users rating forrecommended product. In this research following three novel recommender systems are proposed. These systems are used to investigate issues and challenges related to recommendersystems. Hybrid web personalized recommender system based on web usagemining (HWPRS). Hybrid web personalized recommender system using centeringbunchingbased clustering (CBBCHPRS). Hybrid Fuzzy personalized recommender system using Modified Fuzzyc-means clustering (MFCMHFRS). N� de r�f. du vendeur 9783659877759

Contacter le vendeur