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Distributed Computing Seminar Lecture 5: Graph Algorithms & PageRank Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet Summer 2007 Except as otherwise noted, the content of this presentation is © 2007 Google Inc. and licensed under the Creative Commons Attribution 2.5 License.
Outline ,[object Object],[object Object],[object Object],[object Object]
Motivating Concepts ,[object Object],[object Object],[object Object],[object Object]
Breadth-First Search ,[object Object],[object Object]
Breadth-First Search & MapReduce ,[object Object],[object Object]
Breadth-First Search & MapReduce  ,[object Object],[object Object]
Graph Representations ,[object Object]
Direct References ,[object Object],[object Object],[object Object],[object Object],class GraphNode { Object data; Vector<GraphNode> out_edges; GraphNode  iter_next; }
Adjacency Matrices ,[object Object],[object Object],0 1 0 1 4 0 0 1 0 3 1 1 0 1 2 1 0 1 0 1 4 3 2 1
Adjacency Matrices: Sparse Representation ,[object Object],[object Object],[object Object]
Sparse Matrix Representation ,[object Object],[object Object],[object Object],[object Object]
Sparse Matrix Representation ,[object Object],[object Object],[object Object],[object Object]
Finding the Shortest Path ,[object Object],[object Object],[object Object],This is called the single-source shortest path problem. (a.k.a. SSSP)
Finding the Shortest Path: Intuition ,[object Object],[object Object],[object Object],[object Object],[object Object]
From Intuition to Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object]
What This Gives Us ,[object Object],[object Object],[object Object],[object Object]
Blow-up and Termination ,[object Object],[object Object],[object Object],[object Object],[object Object]
Adding weights ,[object Object],[object Object],[object Object],[object Object]
Comparison to Dijkstra ,[object Object],[object Object],[object Object]
PageRank: Random Walks Over The Web ,[object Object],[object Object],[object Object]
PageRank: Visually
PageRank: Formula ,[object Object],[object Object],[object Object],[object Object],[object Object]
PageRank: Intuition ,[object Object],[object Object],[object Object],[object Object]
PageRank: Issues ,[object Object],[object Object],[object Object]
PageRank: First Implementation ,[object Object],[object Object],[object Object],[object Object]
Distribution of the Algorithm ,[object Object],[object Object],[object Object],[object Object]
Distribution of the Algorithm ,[object Object],[object Object],[object Object],[object Object]
 
Phase 1: Parse HTML ,[object Object],[object Object],[object Object],[object Object]
Phase 2: PageRank Distribution ,[object Object],[object Object],[object Object],[object Object]
Phase 2: PageRank Distribution ,[object Object],[object Object],[object Object],[object Object]
Finishing up... ,[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object]

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Lec5 pagerank

  • 1. Distributed Computing Seminar Lecture 5: Graph Algorithms & PageRank Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet Summer 2007 Except as otherwise noted, the content of this presentation is © 2007 Google Inc. and licensed under the Creative Commons Attribution 2.5 License.
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