PPT-Graph Partitioning

Dr Frank McCown Intro to Web Science Harding University This work is licensed under Creative Commons Attribution NonCommercial 30 Slides use figures from Ch 36 of Networks Crowds and Markets . In this paper we present an algorithm for local graph partitioning using personalized PageRank vectors We develop an improved algorithm for computing approximate PageRank vectors and derive a mixing result for PageRank vectors similar to that for ra Tsourakakis Christos Gkantsidis Bozidar Radunovic Milan Vojnovic November 2012 Technical Report MSRTR2012113 Microsoft Research Microsoft Corporation One Microsoft Way Redmond WA 98052 httpwwwresearchmicrosoftcom C E Tsourakakis is with Carnegie Mel Isabelle Stanton, UC Berkeley. Gabriel . Kliot. , Microsoft Research XCG. Modern graph datasets are huge. The web graph had over a trillion links in 2011. Now?. . facebook. has “more than 901 million users with average degree 130”. C. HEN. , J. IAXIN. S. HI. , Y. ANZHE. C. HEN. , H. AIBO. C. HEN. Institute of Parallel and Distributed Systems. Shanghai Jiao Tong University, China. H. EuroSys 2015. L. Differentiate. d. . Graph Computation and Partitioning on Skewed Graphs. . Oliver Lum. Carmine . Cerrone. Bruce Golden. Edward . Wasil. 1. OAR . Lib Content. Single-Vehicle Solvers. Un/Directed Chinese Postman (UCPP/DCPP). Mixed Chinese Postman (MCPP). C. HEN. , J. IAXIN. S. HI. , Y. ANZHE. C. HEN. , H. AIBO. C. HEN. Institute of Parallel and Distributed Systems. Shanghai Jiao Tong University, China. H. EuroSys 2015. L. Differentiate. d. . Graph Computation and Partitioning on Skewed Graphs. a Multi-Layered Indexing Approach. Yongjiang Liang, . Peixiang Zhao. CS @ FSU. zhao@cs.fsu.edu. Outline. Introduction. State-of-the-art solutions. ML-Index & similarity search. Experiments. Conclusion. Graph Partitioning (cuts, spectral clustering, density), . Community evolution. 1. Introduction. modules, cluster, communities, groups, . partitions (more on this today). 2. Summary of Part I. PART . (in-depth analysis of research literature). 1. Scalable SPARQL Querying of Large RDF Graphs . (aug-sep 2011). 2. Towards Effective Partition Management for Large Graphs . (may 2012). Vineet Choudhury. Graph algorithms . A prototypical graph algorithm: PageRank. In memory. Putting more and more on disk …. Sampling from a graph. What is a good sample? (. graph statistics. ). What methods work? (PPR/RWR). A Game Theoretic . Approach . Proceedings . of the 2015 ACM SIGMOD International Conference on Management of Data. (pp. 1617-1628). . 2016/05/12 M1 . kosaka. Author. Nikos . Armenatzoglou. Ph.D. . at the Department of Computer Science and Engineering, Hong Kong University of Science and . Distributed Graph Analytics. Loc Hoang               Roshan Dathathri. Gurbinder Gill                Keshav Pingali. 1. Distributed Graph Analytics. Analytics on unstructured data. Finding suspicious actors in crime networks. Multi-Cores . With Graph Awareness. Vijayan, Ming, Xuetian, Frank, Lidong, Maya. Microsoft Research. Motivation. Tremendous increase in graph data and applications. New class of graph applications that require real-time responses. William Cohen. Outline. Last week:. PageRank – one sample algorithm on graphs. edges and nodes in memory. nodes in memory. nothing in memory. Aapo. Properties of (social) graphs. GraphLab. /. Powergraph.