This document proposes a novel collaborative filtering-based web service recommender system to help users select services with optimal quality of service (QoS) performance. The recommender system employs location information and QoS values to cluster users and services, and makes personalized recommendations. It achieves considerable improvement in recommendation accuracy compared to existing methods. Comprehensive experiments using over 1.5 million QoS records from real-world web services demonstrate the effectiveness of the approach.