Analysis of Large Graphs

Analysis of these graphs requires introduction of new parameters and methods conceptually different than the ones used for relatively smaller graphs. We describe new parameters and methods for the analysis of these graphs and also describe various models to represent them in this chapter. Two widely...

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Bibliographic Details
Published inGuide to Graph Algorithms pp. 395 - 416
Main Author Erciyes, K
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesTexts in Computer Science
Subjects
Clique-like Structures
Closeness Centrality Values
Edge Betweenness
Eigenvalue Centrality
Vertex Betweenness
Online AccessGet full text
ISBN331973234X
9783319732343
ISSN1868-0941
1868-095X
DOI10.1007/978-3-319-73235-0_13

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Summary:Analysis of these graphs requires introduction of new parameters and methods conceptually different than the ones used for relatively smaller graphs. We describe new parameters and methods for the analysis of these graphs and also describe various models to represent them in this chapter. Two widely used models for the large graphs representing real networks are small-world and scale-free models. The former means the average distance between any two nodes in large graphs is small and only few nodes with high degrees exist with majority of the nodes having low degrees in the latter.
ISBN:331973234X
9783319732343
ISSN:1868-0941
1868-095X
DOI:10.1007/978-3-319-73235-0_13