Friend Recommendation Based on Mobile Crowdsensing in Social Networks

Online Social Network is booming with the development of the hardware and the popularity of the Internet in recent years. Users can invite friends through other users and become friends after consent of each other to share their living information. Here, crowdsensing is adopted by using Bluetooth Low Energy attached on mobile phones to collect proximity sensing information. The online social network data from users is extracted, such as expanding co-friend relationship, establishing a relationship chain through the interaction between friends. In this paper, a strategy is proposed to explore the co-friend's affinity incurring the relationship with common preferences for potential users. The friend recommended weighting strategy is derived to make a recommendation of friends among virtual and real communities. Moreover, the system is designed and implemented to realize in the actual environment and to analyze the data to prove the strategy which helps to find potential friends among users.