论文信息 - A Personalized Recommender System for Telecom Products and Services

A Personalized Recommender System for Telecom Products and Services

The Internet brings excellent opportunities to businesses for providing personalized online services to their customers. Recommender systems are designed to automatically generate personalized recommendations of products and services. This study develops a hybrid recommendation approach which combines user-based and item-based collaborative filtering techniques for mobile product and service recommendation. It particularly implements the approach into an intelligent recommendation system called telecom product recommender system (TCPRS). Experimental results show that the TCPRS can effectively help new customer selecting the most suitable mobile products and services.

Kun Liu | William Wang | Jie Lu | Tai Zhang | Zui Zhang

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