Department of Computer Science University of York

Slides:



Advertisements
Similar presentations
Peer-to-Peer and Social Networks Power law graphs Small world graphs.
Advertisements

Complex Networks Advanced Computer Networks: Part1.
‘Small World’ Networks (An Introduction) Presenter : Vishal Asthana
Small-world networks.
1 Algorithmic Networks & Optimization Maastricht, November 2008 Ronald L. Westra, Department of Mathematics Maastricht University.
Network biology Wang Jie Shanghai Institutes of Biological Sciences.
Emergence of Scaling in Random Networks Albert-Laszlo Barabsi & Reka Albert.
1 Greedy Forwarding in Dynamic Scale-Free Networks Embedded in Hyperbolic Metric Spaces Dmitri Krioukov CAIDA/UCSD Joint work with F. Papadopoulos, M.
Analysis and Modeling of Social Networks Foudalis Ilias.
VL Netzwerke, WS 2007/08 Edda Klipp 1 Max Planck Institute Molecular Genetics Humboldt University Berlin Theoretical Biophysics Networks in Metabolism.
CS 599: Social Media Analysis University of Southern California1 The Basics of Network Analysis Kristina Lerman University of Southern California.
CSE 522 – Algorithmic and Economic Aspects of the Internet Instructors: Nicole Immorlica Mohammad Mahdian.
1 Evolution of Networks Notes from Lectures of J.Mendes CNR, Pisa, Italy, December 2007 Eva Jaho Advanced Networking Research Group National and Kapodistrian.
Directional triadic closure and edge deletion mechanism induce asymmetry in directed edge properties.
Networks. Graphs (undirected, unweighted) has a set of vertices V has a set of undirected, unweighted edges E graph G = (V, E), where.
Networks FIAS Summer School 6th August 2008 Complex Networks 1.
Lecture 9 Measures and Metrics. Structural Metrics Degree distribution Average path length Centrality Degree, Eigenvector, Katz, Pagerank, Closeness,
Identifying Patterns in Road Networks Topographic Data and Maps Henri Lahtinen Arto Majoinen.
Degree correlations in complex networks Lazaros K. Gallos Chaoming Song Hernan A. Makse Levich Institute, City College of New York.
CS 728 Lecture 4 It’s a Small World on the Web. Small World Networks It is a ‘small world’ after all –Billions of people on Earth, yet every pair separated.
Peer-to-Peer and Grid Computing Exercise Session 3 (TUD Student Use Only) ‏
Global topological properties of biological networks.
Search in a Small World JIN Xiaolong Based on [1].
Small World Networks Somsubhra Sharangi Computing Science, Simon Fraser University.
Network analysis and applications Sushmita Roy BMI/CS 576 Dec 2 nd, 2014.
On Distinguishing between Internet Power Law B Bu and Towsley Infocom 2002 Presented by.
Peer-to-Peer and Social Networks Random Graphs. Random graphs E RDÖS -R ENYI MODEL One of several models … Presents a theory of how social webs are formed.
Optimization Based Modeling of Social Network Yong-Yeol Ahn, Hawoong Jeong.
Information Networks Power Laws and Network Models Lecture 3.
(Social) Networks Analysis III Prof. Dr. Daning Hu Department of Informatics University of Zurich Oct 16th, 2012.
LANGUAGE NETWORKS THE SMALL WORLD OF HUMAN LANGUAGE Akilan Velmurugan Computer Networks – CS 790G.
Small-world networks. What is it? Everyone talks about the small world phenomenon, but truly what is it? There are three landmark papers: Stanley Milgram.
Clustering of protein networks: Graph theory and terminology Scale-free architecture Modularity Robustness Reading: Barabasi and Oltvai 2004, Milo et al.
COLOR TEST COLOR TEST. Social Networks: Structure and Impact N ICOLE I MMORLICA, N ORTHWESTERN U.
Gennaro Cordasco - How Much Independent Should Individual Contacts be to Form a Small-World? - 19/12/2006 How Much Independent Should Individual Contacts.
Social Network Analysis Prof. Dr. Daning Hu Department of Informatics University of Zurich Mar 5th, 2013.
3. SMALL WORLDS The Watts-Strogatz model. Watts-Strogatz, Nature 1998 Small world: the average shortest path length in a real network is small Six degrees.
Algorithms for Biological Networks Prof. Tijana Milenković Computer Science and Engineering University of Notre Dame Fall 2010.
Networks Igor Segota Statistical physics presentation.
Efficient Labeling Scheme for Scale-Free Networks The scheme in detailsPerformance of the scheme First we fix the number of hubs (to O(log(N))) and show.
Neural Network of C. elegans is a Small-World Network Masroor Hossain Wednesday, February 29 th, 2012 Introduction to Complex Systems.
Complex Network Theory – An Introduction Niloy Ganguly.
Class 9: Barabasi-Albert Model-Part I
Complex Network Theory – An Introduction Niloy Ganguly.
CCR = Connectivity Residue Ratio = Pr. [ node pair connected by an edge are together in a common page on computer disk drive.] “U of M Scientists were.
1 CIS 4930/6930 – Recent Advances in Bioinformatics Spring 2014 Network models Tamer Kahveci.
March 3, 2009 Network Analysis Valerie Cardenas Nicolson Assistant Adjunct Professor Department of Radiology and Biomedical Imaging.
Informatics tools in network science
Project 1 : Phase 1 22C:021 CS II Data Structures.
An Improved Acquaintance Immunization Strategy for Complex Network.
Algorithms and Computational Biology Lab, Department of Computer Science and & Information Engineering, National Taiwan University, Taiwan Network Biology.
Structures of Networks
Hiroki Sayama NECSI Summer School 2008 Week 2: Complex Systems Modeling and Networks Network Models Hiroki Sayama
Biological networks CS 5263 Bioinformatics.
Empirical analysis of Chinese airport network as a complex weighted network Methodology Section Presented by Di Li.
Assessing Hierarchical Modularity in Protein Interaction Networks
Network Science: A Short Introduction i3 Workshop
Section 8.6 of Newman’s book: Clustering Coefficients
The Watts-Strogatz model
Section 8.2: Shortest path and small world effect
Shortest path and small world effect
Peer-to-Peer and Social Networks Fall 2017
Small World Networks Scotty Smith February 7, 2007.
Network Science: A Short Introduction i3 Workshop
Topology and Dynamics of Complex Networks
Clustering Coefficients
Peer-to-Peer and Social Networks
Degree Distributions.
Section 8.3: Degree Distribution
Local Clustering Coefficient
Presentation transcript:

Department of Computer Science University of York Complex Network Department of Computer Science University of York

Network in Life

Network

Basic Concepts Average Path Length the mean distance between two nodes, averaged over all pairs of nodes. Clustering Coefficient the average fraction of pairs of neighbors of a node that are also neighbors of each other. Degree Distribution The spread of node degrees over a network is characterized by a distribution function P(k)

Network Models Random Graphs Small-World Model Scale-Free Model

Thank you Complex Network Find out more at the PowerPoint Getting Started Center

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2025 SlidePlayer.com. Inc. All rights reserved.