Complex Networks

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A01=Kayhan Erciyes
adjacency
advanced complex network analysis techniques
algorithm
Algorithmic aspects of complex network analysis
Author_Kayhan Erciyes
Be
BFS Algorithm
BFS Tree
Biological networks
Bipartite Graph
Category=PBD
Category=PBV
Category=UMB
Category=UT
Category=UYF
clustering
Clustering Coefficient
clusters
Community Detection
Complex networks
computational network analysis
directed
discrete mathematics applications
distributed systems research
DS
Edge Betweenness
Eigenvalue Centrality
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
graph
Graph G1
Graph theory
Hamiltonian Path
matrix
Minimal VC
Network Alignment
Network Motifs
Network science
parallel algorithm design
PPI Network
Preferential Attachment Rule
Protein Interaction Network
random
Sample Graph
Shortest Paths
Small World Network
social network modeling
Subgraph Isomorphism
undirected
Undirected Graph
Unweighted Graph
VC
vertex
Weighted Graph
wireless network algorithms

Product details

  • ISBN 9781466571662
  • Weight: 589g
  • Dimensions: 156 x 234mm
  • Publication Date: 06 Sep 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Network science is a rapidly emerging field of study that encompasses mathematics, computer science, physics, and engineering. A key issue in the study of complex networks is to understand the collective behavior of the various elements of these networks.

Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, few books focus on the algorithmic aspects of complex network analysis. Filling this need, Complex Networks: An Algorithmic Perspective supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher and student of complex networks.

This book is about specifying, classifying, designing, and implementing mostly sequential and also parallel and distributed algorithms that can be used to analyze the static properties of complex networks. Providing a focused scope which consists of graph theory and algorithms for complex networks, the book identifies and describes a repertoire of algorithms that may be useful for any complex network.

  • Provides the basic background in terms of graph theory
  • Supplies a survey of the key algorithms for the analysis of complex networks
  • Presents case studies of complex networks that illustrate the implementation of algorithms in real-world networks, including protein interaction networks, social networks, and computer networks

Requiring only a basic discrete mathematics and algorithms background, the book supplies guidance that is accessible to beginning researchers and students with little background in complex networks. To help beginners in the field, most of the algorithms are provided in ready-to-be-executed form.

While not a primary textbook, the author has included pedagogical features such as learning objectives, end-of-chapter summaries, and review questions

Kayhan Erciyes is a professor of computer science and engineering and also the rector of Izmir University, Izmir, Turkey. Dr. Erciyes worked as a research and development engineer of Alcatel Turkey, Alcatel Portugal, and Alcatel SEL. He has worked as faculty in Oregon State University, UC Davis and California State University, US and Izmir and Aegean universities. His research interests are on distributed systems, graph theory and distributed algorithms for complex networks, mobile ad hoc networks, wireless sensor networks and the Grid and has published extensively in these areas. Dr. Erciyes is the designer and implementer of one of the first commercially available MODEMs in Turkey

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