SocialFusion: Context-Aware Inference and Recommendation By Fusing Mobile, Sensor, and Social Data

Mobile social networks are rapidly becoming an important new domain showcasing the power of mobile computing systems. These networks combine mobile location information with social networking data to enable fully context-aware environments. This paper proposes SocialFusion, a framework to support context-aware inference and recommendation by fusing together mobile, sensor, and social data. We investigate a case study of SocialFusion that enables an application for group-based context-aware video. We show how SocialFusion can be used to gather mobile, sensor, and social data, infer group descriptors, and then apply these meta-level descriptors to improve the recommendation of video playback for a group of users viewing the same screen.