fast-ppr: personalized pagerank estimation for large graphs

FAST-PPR: Personalized PageRank Estimation for Large Graphs

Peter Lofgren (Stanford)Joint work with Siddhartha Banerjee (Stanford), Ashish Goel (Stanford), and C. Seshadhri (Sandia)

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Motivation: Personalized Search

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Motivation: Personalized SearchRe-ranked by PPR

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Result Preview

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6 min1.2 hour

Fast-PPR Monte-Carlo

Local-Update

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Personalized PageRank

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Goal

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Previous Algorithm: Monte-CarloPrevious Algorithm: Monte-Carlo[Avrachenkov, et al 2007]

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Previous Algorithm: Local Update[Anderson, et al 2007]

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Main Result

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Analogy: Bidirectional Search

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Bidirectional PageRank Algorithm

Reverse Work(Frontier Discovery)

Forward Work(Random Walks)

u

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Main Idea

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Experimental Setup

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Empirical Running Time

Log Scale

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Summary

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Thank You

• Paper available on Arxiv• Code available at cs.stanford.edu/~plofgren

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Frontier is Important

FrontierAidedSignificanceThresholding

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Algorithm (Simple Version)

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Algorithm (Simple Version)

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Average Running Time

Reverse Work (Local Update)

Forward Work (Monte-Carlo)

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Correctness

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Algorithm (Theoretical Version)

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Algorithm (Theoretical Version)

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Local Update Algorithm

Uu Uv2

Uv3

Ut

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Local Update Algorithm

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Local Update Algorithm