PPT-Modularity and Community Structure in Networks* M.E.J Newman in

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Modularity and Community Structure in Networks MEJ Newman in PNAS 2006 1 Networks A network presented by a graph G VE V nodes E edges link node pairs Examples

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Modularity and Community Structure in Networks* M.E.J Newman in: Transcript

Modularity and Community Structure in Networks MEJ Newman in PNAS 2006 1 Networks A network presented by a graph G VE V nodes E edges link node pairs Examples of reallife networks. by Optimizing Community Quality Metrics. Mingming. Chen. Department of Computer Science. Rensselaer . Polytechnic . Institute. 09/28/2015. Community Structure. Community is the basic structure in many networks. M.E.J. Newman in . PNAS. 2006. 1. Networks. A network: presented by a graph G(. V,E. ):. V = nodes, E = edges (link node pairs). Examples of real-life networks: . social networks (V = people) . World Wide Web (V= . Jure Leskovec, CMU. Kevin Lang, Anirban Dasgupta and Michael Mahoney. Yahoo! Research. Network communities. Communities:. Sets of nodes with . lots. of connections . inside. and . few . to . outside. Jure Leskovec, CMU. Kevin Lang, Anirban Dasgupta, Michael Mahoney. Yahoo! Research. Networks. Big data. Study emerging behaviors. How are small networks different from large. 2. Network community structure. Automated Software Design. Don Batory. Department of Computer Science. University of Texas At Austin. Modularity15-. 1. Salutes. Modularity15-. 2. Robert France . Leonard . Nimoy. Introduction. I have worked in modeling and modularity . CS. . 111. On-Line MS Program. Operating . Systems . Peter Reiher. . Introduction. Most useful abstractions an OS wants to offer can’t be directly realized by hardware. The hardware doesn’t do exactly what the abstraction requires. Vaibhav. . Mallya. EECS 767. D. . Radev. 1. Agenda. Agenda. Basic Definitions. Girvan-Newman Algorithm. Donetti. -Munoz Spectral Method. Karypis. -Kumar Multi-level Partitioning. Graclus. GraphClust. Jure Leskovec, CMU. Kevin Lang, Anirban Dasgupta and Michael Mahoney. Yahoo! Research. Network communities. Communities:. Sets of nodes with . lots. of connections . inside. and . few . to . outside. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. Computer Sciences 838. https://compnetbiocourse.discovery.wisc.edu. Nov 1. st. 2016. Some material is adapted from lectures from Introduction to Bioinformatics. Application to voting patterns in the US Senate. Based on . “Sequential . detection of temporal communities . by . estrangement . confinement”. Kawadia. , Sreenivasan, . Sci. Rep. . 1. :794 (2015). By: Ralucca Gera, . Applied math department,. Naval Postgraduate School. Monterey, CA, USA. Why?. Mostly observed real networks have:. Heavy tail (. powerlaw. most probably, exponential). High clustering (high number of triangles especially in social networks, lower count otherwise). Monterey, California. rgera@nps.edu. Overview of. Communities in networks. What is a community?. A community . ~ a group of people with common characteristic or shared interests. What do they correspond to?. Core-periphery structure. Excellence Through Knowledge. Prof. Ralucca Gera, rgera@nps.edu . Applied Mathematics Department, . Naval Postgraduate School. Learning Outcomes. Understand and contrast the different k-clique relaxation definitions:. Sushmita Roy. sroy@biostat.wisc.edu. Computational Network Biology. Biostatistics & Medical Informatics 826. https://compnetbiocourse.discovery.wisc.edu. Nov 1. st. 2018. Goals for today. Finding modules on graphs/Community structure on graphs/Graph clustering.

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