TY - JOUR AB - 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. © 2012 Elsevier Inc. All rights reserved. AU - Zhang, Z AU - Lin, H AU - Liu, K AU - Wu, D AU - Zhang, G AU - Lu, J DA - 2013/06/20 DO - 10.1016/j.ins.2013.01.025 EP - 129 JO - Information Sciences PY - 2013/06/20 SP - 117 TI - A hybrid fuzzy-based personalized recommender system for telecom products/services VL - 235 Y1 - 2013/06/20 Y2 - 2024/03/28 ER -