PPT-Community Structure in Large Complex Networks

Liaoruo Wang and John E Hopcroft Dept of Computer Engineering amp Computer Science Cornell University In Proc 7th Annual Conference on Theory and Applications of Models of Computation TAMC. stny 1A H1117 Budapest Hungary Dept of Biological Physics E otv os University P azm any P stny 1A H1117 Budapest Hungary Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections amon classical/quantum . phase transitions. Ginestra . Bianconi. . Department of Physics, Northeastern . University, Boston. ETC Trento Workshop. Spectral properties of complex networks . Trento 23-29 July, . 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. Dima. . Volchenkov. A . network . is . any method of sharing information. . . between . systems consisting of many individual . units . V. , . a . A. W. Schreiber. Australian Centre for Plant Functional Genomics. Waite Campus, . University of Adelaide. Achievements and new directions. in Subatomic Physics:. Workshop in Honour of Tony . Thomas’s 60. 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. 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?. Monojit . Choudhury. Microsoft Research India. monojitc@microsoft.com. . . light. color. red. blue. blood. sky. heavy. weight. 100. 20. 1. NLP vs. Computational Linguistics. Computational Linguistics is the study of . 680 Structure 1994, Vol 2 No 7[28-30], squash seed trypsin inhibitor (squash seedinhibitor family; [31]), serpins [32-38] and hirudin[39,40]. The inhibitors from these different familieshave a common 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:.