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, �berseering 33, 22297 Hamburg 140 pp. Englisch.

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Bibliographic Details

Title: Web personalized Recommender System for e-business
Publisher: LAP LAMBERT Academic Publishing M�r 2018
Publication Date: 2018
Language: English
ISBN 10: 3659877751
ISBN 13: 9783659877759
Binding: Taschenbuch
Condition: Neu
Dimensions: 220 millimeters width by 150 millimeters height by 9 millimeters depth
Weight: 227 grams

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