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Web personalized Recommender System for e-business
Publicado por
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659877751
ISBN 13: 9783659877759
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: 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 . Nº de ref. del artículo: 385770109
Cantidad disponible: Más de 20 disponibles
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Web personalized Recommender System for e-business
Publicado por
LAP LAMBERT Academic Publishing Mrz 2018, 2018
ISBN 10: 3659877751
ISBN 13: 9783659877759
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659877759
Cantidad disponible: 2 disponibles
Imagen del vendedor
Web personalized Recommender System for e-business
Publicado por
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659877751
ISBN 13: 9783659877759
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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). Nº de ref. del artículo: 9783659877759
Cantidad disponible: 1 disponibles
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Web personalized Recommender System for e-business
Publicado por
LAP LAMBERT Academic Publishing Mär 2018, 2018
ISBN 10: 3659877751
ISBN 13: 9783659877759
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659877759
Cantidad disponible: 2 disponibles
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Web personalized Recommender System for e-business
Publicado por
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659877751
ISBN 13: 9783659877759
Nuevo
Paperback
Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. Nº de ref. del artículo: 3659877751
Cantidad disponible: 1 disponibles