Building Mobile Social Network with Semantic Relation Using Bayesian NeTwork-based Life-log Mining

Mobile devices such as cell phone, PDA and smart phone have been so popularized that they are to be a necessity for everyday life. These mobile devices can be very useful tools to collect users´ life-logs because they have many sensors and users always carry them. Therefore, many studies using mobile life-logs are actually being conducted. Mobile life-logs include interaction information between users as well as personal information of each user. We collect these mobile life-logs, and additionally, high-level logs such as activity and emotion as helping users to annotate them. Based on these life-logs, we build a novel mobile social network by mining semantic relations between users in life-logs using Bayesian network. For experiments, we build the mobile social networks and analyze them. Finally, we discuss how this mobile social network can be used for practical application and implemented a proof-of-concept application.