Along with the development of wireless communication technologies and smart mobile devices, location-based services (LBS), with its characteristics of mobility, practicality, momentary and personalization, has been widely applied in military, transportation, logistics etc, and it has become one of the most potential mobile value-added services. Based on a proposed framework of location-based network services recommendation, this paper first provides an approach to compute mobile users' preferences similarity from their geographic location, and proves that it satisfies the general properties of neighbor similarity measure. Then according with the concept of trust in sociology, a new method is presented for calculating trust value. By importing them into network services recommendation process, an approach of location-based network services recommendation is proposed, which effectively improves its accuracy and reliability, and mitigates data sparsity of users' similarity matrix and cold start users problem in recommendation process. Finally the proposed algorithm is proved to be more accurate and feasible in experiments by using the public dataset MIT.