19-page_rank_annot

19-page_rank_annot -...

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CS224W: Social and Information Network Analysis re eskovec tanford University Jure Leskovec, Stanford University http://cs224w.stanford.edu
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ow organize/navigate it? How to organize/navigate it? First try: Web directories Yahoo, DMOZ, okSmart LookSmart 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 2
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EARCH! SEARCH! Find relevant docs in a small and trusted set: Newspaper articles atents, etc Patents, etc. Two traditional problems: Synonimy: buy – purchase, sick – ill Polysemi: jaguar 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 3
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Does more documents mean better results? 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 4
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hat is “best” answer to query “Stanford”? What is best answer to query Stanford ? Anchor Text: I go to Stanford where I study hat about query “newspaper”? What about query newspaper ? No single right answer arcity R) vs bundance eb f information Scarcity (IR) vs. abundance (Web) of information Web: Many sources of information. Who to “trust” ick: Trick: Pages that actually know about newspapers ight all be pointing to many newspapers might all be pointing to many newspapers Ranking! 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 5
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oal ack to e newspaper ample): Goal (back to the newspaper example): Don’t just find newspapers.Find “experts”–people who link in a coordinated way to good newspapers ea: nks as votes Idea: Links as votes Page is more important if it has more links In coming links? Out going links? Hubs and Authorities Quality as an expert ( hub ): NYT: 10 Ebay: 3 Total sum of votes of pages pointed to Quality as an content ( authority ): tal sum of votes of experts Yahoo: 3 CNN: 8 Total sum of votes of experts Principle of repeated improvement 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu WSJ: 9 6
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11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 7
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11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 8
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11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 9
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[Kleinberg ‘98] ach page as 2 kinds of scores: Each page i has 2 kinds of scores: Hub score: h i Authority score : a i HITS algorithm: Initialize: a =h =1 i i Then keep iterating: Authority : Hub : j i i j h a j i j i a h Normalize: a i =1, h i =1 11/29/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 10
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[Kleinberg ‘98] ITS converges a single stable point HITS converges to a single stable point Slightly change the notation: ector =(a a h= (h Vector a=(a 1 …,a n ), h=(h 1 …,h n ) Adjacency matrix ( n x n ): M
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19-page_rank_annot -...

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