The paper was written by Kang Zhao and Xi Wang, University of Iowa Mo yu, Penn State University Bo Gao, Beijing Jiaotong University I just presented for completing my undergrad course

1. User Recommendations in
Reciprocal and Bipartite Social
Networks
An online Dating Case Study
Presented by: Md. Kamruzzaman

2. Authors
Kang Zhao and Xi Wang, University of Iowa
Mo yu, Penn State University
Bo Gao, Beijing Jiaotong University

3. Social Network
• Facebook, LinkedIn,Twitter.
• Billions of user.
• Huge revenue opportunity.
• Vast impact on social life.

4. Reciprocal Network
User

5. Bipartite Network
• Paper-Author network.
• Audience-Movie network.
User Target

6. Reciprocal & Bipartite Network
• Online Dating Site, Matrimony Site.
• Both reciprocal and bipartite network exist.

7. Goal
• Authors take online dating site for the research.
• Better user recommendation is the ultimate goal.

8. User Recommendation
• Freinds of friends is the most popular method.
• FoF is not possible for Reciprocal – bipartite network.
• Existing system deals with explicit profile. Such as profession, age.
• In this method, authors tried to find out a new way other than using
explicit profile.

9. Three Model System
• Baseline CF Model
• Reciprocity-Only Model
• Hybrid Model

10. Scenario

11. Baseline CF Model

12. Reciprocity Only Model

13. Hybrid Model

14. Calculation
• User, p
• Target user, t
Using this formula given a success score for target user, the higher the
score, the higher probability of recommendation.

15. Evaluation
• Two sets of metrics to evaluate
• Initial contact
-IC precision@k
-IC recall@k
• Reciprocal contact
-RC precision@k
-RC recall@k

16. Result

17. Result

18. Final Words
• According to experiment, Hybrid Model is more successful approach.
• Can be applied in university admission network, job hunting network.
• Use of sensitivity analysis can make HM more robust.

19. Thank You