20-link_pred_annot

20-link_pred_annot - CS224W:...

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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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[LibenNowell Kleinberg ‘03] nk prediction task: Link prediction task: Given G[t 0 ,t 0 ’] a graph on edges up to time t 0 utput a ranked list f links (not in [t that output a ranked list L of links (not in G[t 0 ,t 0 ] ) that are predicted to appear in G[t 1 ,t 1 ’] Evaluation: n=|E new | : # new edges that appear during the test period [t 1 ,t 1 ’] Take top n elements of L and count correct edges 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 2
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[LibenNowell Kleinberg ‘03] nk prediction task: Link prediction task: Given G[t 0 ,t 0 ’] a graph on edges up to time t 0 utput a ranked list f links (not in [t that output a ranked list L of links (not in G[t 0 ,t 0 ] ) that are predicted to appear in G[t 1 ,t 1 ’] Evaluation: n=|E new | : # new edges that appear during the test period [t 1 ,t 1 ’] Take top n elements of L and count correct edges 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 3
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[LibenNowell Kleinberg ‘03] redict links evolving collaboration network Predict links evolving collaboration network Core: Since network data is very sparse Consider only nodes with in degree and out degree of at least 3 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 4
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[LibenNowell Kleinberg ‘03] r every pair of nodes ( y compute: Γ (x) … degree of node x For every pair of nodes (x,y) compute: Sort the pairs by score and di t t i li k predict top n pairs as new links 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 5 Γ (x) … degree of node x
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[LibenNowell Kleinberg ‘03] ank potential links ( y based on: Rank potential links (x,y) based on: 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 6 Γ (x) … degree of node x
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12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 7
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[LibenNowell Kleinberg ’ 03] 12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 8
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12/01/2010 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 9 Improvement over #common neighbors
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ecommend a list of possible friends Recommend a list of possible friends Supervised machine learning setting: Training example: For every node s have a list of nodes she will create links to {v 1 , …, v k } roblem: Problem: Learn a model that will for a given node s rank nodes {v 1 , …, v k } higher an other nodes in the network than other nodes in the network How to combine node/edge attributes and network structure?
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This note was uploaded on 01/11/2011 for the course CS 224 at Stanford.

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20-link_pred_annot - CS224W:...

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