1. Location Prediction on Location Based Social Network Lau Chun Ki

2. Outline 1. Location 3: How Users Share and Respond to Location-Based Data on Social Networking Sites (Jonathan Chang, Eric Sun) 2. Addressing the Cold-Start Problem in Location Recommendation Using Geo-Social Correlations (Huiji Gao, Jilliang Tang, Huan Liu)

3. Location-Based Social Network

4. Location 3: How Users Share and Respond to Location-Based Data on Social Networking Sites 1. Location 2. Response 3. Friendship

5. Major Findings

6. What About a New Place? Location Prediction User’s Previous Check-in Record Friends Check-in Record

7. COLD-START PROBLEM

8. Addressing the Cold-Start Problem in Location Recommendation Using Geo- Social Correlations gSCorr Geo-social Circles –Geographic factor (D: Distant) –Social factor (F: Friends)

9. Geo-social Circles

10. Location Recommendation

14. 1.Location Frequency (LF) 2.User Frequency (UF)

15. Example: Predict for Location E S.NLF S.UF LF.UF = LF x UFS.LF.UF NLF.UF = NLF x UFS.NLF.UF

17. Comparison & Evaluation PSMM: Periodic & Social Mobility Model SHM: Social-Historical Model CF: Collaborative Filtering gSCorr: Geo-Social Correlation

18. Contribution from Different Circles

19. Limitations Discrete Distant Diminishing Influence