1. FAST-PPR: Personalized PageRank Estimation for Large Graphs Peter Lofgren (Stanford) Joint work with Siddhartha Banerjee (Stanford), Ashish Goel (Stanford), and C. Seshadhri (Sandia)

2. Motivation: Personalized Search 2

3. 3 Re-ranked by PPR

4. Result Preview 4 2 sec 6 min 1.2 hour Fast-PPRMonte- Carlo Local- Update

5. Personalized PageRank 5

6. Goal 6

7. Previous Algorithm: Monte-Carlo 7 [Avrachenkov, et al 2007]

8. Previous Algorithm: Local Update 8 [Anderson, et al 2007]

9. Main Result 9

10. Analogy: Bidirectional Search 10

11. Bidirectional PageRank Algorithm 11 Reverse Work (Frontier Discovery) Forward Work (Random Walks) u

12. Main Idea 12

13. Experimental Setup 13

14. Empirical Running Time 14 Log Scale

15. Summary 15

16. Thank You Paper available on Arxiv Code available at cs.stanford.edu/~plofgren cs.stanford.edu/~plofgren 16

17. 17

18. Frontier is Important 18 Frontier Aided Significance Thresholding

19. Algorithm (Simple Version) 19

20. Algorithm (Simple Version) 20

21. Average Running Time 21 Reverse Work (Local Update) Forward Work (Monte-Carlo)

22. Correctness 22

23. Algorithm (Theoretical Version) 23

24. 24 Algorithm (Theoretical Version)

25. v1v1 Local Update Algorithm 25 U u U v2v2 U v3v3 U t

26. Local Update Algorithm 26

27. Local Update Algorithm 27