Abstract: Existing social networking services recommend friends to users based on their social graphs, which may not be the most appropriate to reflect a userís preferences on friend selection in real life. we present Friendbook, a novel semantic-based friend recommendation system for social networks, which recommends friends to users based on their life styles instead of social graphs. By taking advantage of sensor-rich smart phones, Friendbook discovers life styles of users from user-centric sensor data, measures the similarity of life styles between users, and recommends friends to users if their life styles have high similarity. Inspired by text mining, we model a userís daily life as life documents, from which his/her life styles are extracted.

Keywords: GCM- Google Cloud Messaging, JSON- Java Script Object Notation, GPS- Global Positioning System, Text mining.