Articles liés à Web personalized Recommender System for e-business
Acheter neuf
Afficher cet article
EUR 46,18
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisRésultats de recherche pour Web personalized Recommender System for e-business
Image fournie par le vendeur
Web personalized Recommender System for e-business
Edité par
LAP LAMBERT Academic Publishing, 2018
ISBN 10 : 3659877751
ISBN 13 : 9783659877759
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 385770109
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Web personalized Recommender System for e-business
Edité par
LAP LAMBERT Academic Publishing, 2018
ISBN 10 : 3659877751
ISBN 13 : 9783659877759
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 9783659877759
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Web personalized Recommender System for e-business
Edité par
LAP LAMBERT Academic Publishing Mrz 2018, 2018
ISBN 10 : 3659877751
ISBN 13 : 9783659877759
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 9783659877759
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Web personalized Recommender System for e-business
Edité par
LAP LAMBERT Academic Publishing Mär 2018, 2018
ISBN 10 : 3659877751
ISBN 13 : 9783659877759
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. 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).Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. N° de réf. du vendeur 9783659877759
Quantité disponible : 2 disponible(s)
Image d'archives
Web personalized Recommender System for e-business
Edité par
LAP LAMBERT Academic Publishing, 2018
ISBN 10 : 3659877751
ISBN 13 : 9783659877759
Neuf
Paperback
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. N° de réf. du vendeur 3659877751
Quantité disponible : 1 disponible(s)