Existing social networking services recommend friends to users based on their social graphs, which may not be the most appropriate to reflect a user’s preferences on friend selection in real life. In this paper, 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 smartphones, 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 user’s daily life as life documents, from which his/her life styles are extracted by using the Latent Dirichlet Allocation algorithm. We further propose a similarity metric to measure the similarity of life styles between users, and calculate users’ impact in terms of life styles with a friend-matching graph. Upon receiving a request, Friendbook returns a list of people with highest recommendation scores to the query user. Finally, Friendbook integrates a feedback mechanism to further improve the recommendation accuracy. We have implemented Friendbook on the Android-based smartphones, and evaluated its performance on both small-scale experiments and large-scale simulations. The results show that the recommendations accurately reflect the preferences of users in choosing friends.

  • Project Category : IEEE Projects
  • Project Year : 2015-2016
  • Department
  • Any degree, B.E (civil), B.E(Aeronautical Engineering), B.E(Automobile), B.E(Bio Medical Engg), B.E(Computer Science) , B.E(Electrical and Electronics Engg), B.E(Electronics and Communication), B.E(Information Technology), B.E(Instrumentation Control and Engg), B.E(Mechanincal Engineering), B.E(Mechtronics), B.SC(CS), B.SC(IT), B.Tech, BCA, M.E(APPLIED ELECTRONICS), M.E(Computer Science), M.E(CONTROL SYSTEM), M.E(Mechanical Engineering), M.E(POWER ELECTRONICS), M.E(SOFTWATE ENGG), M.E(VLSI), M.SC(CS&M), M.SC(CS), M.SC(IT&M), M.SC(IT), M.SC(SOFTWARE ENGG), M.Tech, MCA,
  • Domain
  • Cloud Computing, Embedded system, MATLAB Projects, Mobile Computing, Networking,
  • Technology
  • C, C++, .Net, J2EE, Java,
  • Avilable city
  • Ahmedabad, Bangalore, Chennai, Coimbatore, Davangere, Delhi, Dharmapuri, Ernakulam, Hyderabad, Kolkata, Kozhikode, Madurai, Mumbai, Pondicherry, Pune, Salem, Thanjavur, Tirunelveli, Trichy, Vellore,


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