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A hybrid fuzzy-based personalized recommender system for telecom products/services

Authors
Journal
Information Sciences
0020-0255
Publisher
Elsevier
Publication Date
Volume
235
Identifiers
DOI: 10.1016/j.ins.2013.01.025
Keywords
  • Recommender System
  • Telecom Product/Service
  • Web Personalization
  • Collaborative Filtering
  • Fuzzy Set
Disciplines
  • Design

Abstract

Abstract The Internet creates excellent opportunities for businesses to provide personalized online services to their customers. Recommender systems are designed to automatically generate personalized suggestions of products/services to customers. Because various uncertainties exist within both product and customer data, it is a challenge to achieve high recommendation accuracy. This study develops a hybrid recommendation approach which combines user-based and item-based collaborative filtering techniques with fuzzy set techniques and applies it to mobile product and service recommendation. It particularly implements the proposed approach in an intelligent recommender system software called Fuzzy-based Telecom Product Recommender System (FTCP-RS). Experimental results demonstrate the effectiveness of the proposed approach and the initial application shows that the FTCP-RS can effectively help customers to select the most suitable mobile products or services.

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