1. Topic-Sensitive PageRank Taher H. Haveliwala Stanford University Presentation by Na Dai

2. The frame of system using topic-sensitive PageRank

3. PageRank Rank is a n-dimension column vector of PageRank values.(i.e. Rank = (Rank(1), Rank(2),…, Rank(n)) T Motivation: irreducible & aperiodic –Dangling node (Matrix D) –Damp factor α(Matrix E)

4. Topic-Sensitive PageRank (1) w (w1, w2,…,w16): a normalized vector with length 1 wi = Pr(ci|q)

5. Topic-Sensitive PageRank (2)

6. Effect of ODP-Biasing (1)

7. Effect of ODP-Biasing (2)

8. Effect of ODP-Biasing (3)

9. Query-sensitive Scoring

11. Future Work Investigate the best basis topics –Topic granularity –Topics that are deeper in hierarchy vj: resistant to adversarial ODP editors