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AUTHORITATIVE SOURCES IN HYPERLINKED ENVIRONMENT

AUTHORITATIVE SOURCES IN HYPERLINKED ENVIRONMENT. By Jon M. Kleinberg Presented by Moonyoung Kang. Warnings. S tatements might be strong. Argue me back. Correct me if wrong. Slides are razzle -dazzling. Keep your attention. Old tech (1998). We know the result

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AUTHORITATIVE SOURCES IN HYPERLINKED ENVIRONMENT

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  1. AUTHORITATIVE SOURCES IN HYPERLINKED ENVIRONMENT By Jon M. Kleinberg Presented by Moonyoung Kang

  2. Warnings • Statements might be strong. • Argue me back. • Correct me if wrong. • Slides are razzle-dazzling. • Keep your attention.

  3. Old tech (1998) • We know the result • Presentation focus: Who won? Why?

  4. Paper talks about… Hubs & Authorities Clustering Page Similarity

  5. I will focus on… Hubs & Authorities

  6. What Instructors Want Don’t forget Ranking Nodes

  7. Hubs & Authorities In 5 slides

  8. What is “Hubs & Authorities” • Finding important & relevant nodes • Hubs (outlinks) • Authorities (inlinks)

  9. Relevance Query Seed Matching terms

  10. Outlink 1 1 1 1 Hub scores authority

  11. Inlink 1 1 1 1 Authority scores hub

  12. Stationary state Hubs & Authorities In 5 slides Converge

  13. 1998 & 2013

  14. It is a period of node-ranking war. • PAGERANK and HITS knew each other

  15. It’s 2013. Who won?

  16. What Google Scholar says… 7751 6380

  17. What People think…

  18. Why? Similar? Different? Hubs & Authorities

  19. Similarities… Iterative Adj. Matrix Eigenvector Link to Scores

  20. Easy differences… Adj.Matrix Two scores Single score Voting

  21. What Jon says… Query dep. Two-degree model Local Query indep. One-degree model Global

  22. HiTsvspagerank

  23. #1 Query dependent search = = + Is this good or bad?

  24. Variance = = High = = Low + + = = High 24

  25. #2 Local computation Fast Do you buy this? Google’s solution?

  26. Visit all nodes, eventually. In & Out links Web is connected

  27. Who’s faster to USERs?

  28. Multi-users? … …

  29. MapReduce (2004)

  30. #3 Two-degree model Do you buy this? WWW divisible into Hubs & Authorities

  31. Bipartite How Jon thinksweb looks like How web reallylooks like

  32. Conclusion • PageRank beats HITS in many ways… • REAL WORLD ≠ PAPER • Arguments may be misleading • Don’t share this presentation publicly • Jon hates this

  33. Special thanx to…

  34. Questions?

  35. END OF SLIDES

  36. A long time ago in a lab far, far away....

  37. Everybody talks about …

  38. What do YOU think?

  39. Who’s faster to USERS?

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