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Location-based services have faced a development from being a hype to be used by a large user community at any place and time. However, only a few approaches exist, that take into account social interactions and learn from them in order to refine recommendations of points of interests accordingly. This paper analyzes the influence factors of mobile users for the choice of interests and derives an...
This paper introduces a preliminary approach and evaluation for a social recommendation mechanism for location-based services (LBS). Many approaches for recommending location-based services do not take into account other factors than spatial ones. This paper focuses on social interactions and a focused ranking method to support social recommendations. The qualitative and quantitative evaluation at...
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