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Core Decomposition of Massive, Information-Rich Graphs

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Encyclopedia of Social Network Analysis and Mining

Synonyms

Core graph decomposition; k-Core decomposition; k-Coreness; k-Cores; k-Shell decomposition

Glossary

Core decomposition:

The set of all k-cores of a graph, for all k

Core number (or core index):

For each vertex of a graph, the highest order of a core containing that vertex

Degeneracy:

The highest order of a core of a graph. It corresponds to the maximum core number over all vertices of the graph

Distributed graph:

Graph that is stored across multiple machines

Graph (or network):

A set of objects (called vertices or nodes) connected to each other by links (also known as edges or arcs). Links can be represented as unordered or ordered pairs of vertices. In the former case, the graph is said to be undirected, otherwise it is directed. Links may be assigned weights. In this case, the graph is said weighted

k-core (or core of order k):

Maximal subgraph where each vertex is connected to at least k other vertices within the subgraph

k-shell:

Subgraph induced by all vertices belonging...

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Author information

Authors and Affiliations

  1. ISI Foundation, Turin, Italy

    Francesco Bonchi

  2. UniCredit, R&D Dept, Rome, Italy

    Francesco Gullo

  3. Eurecat, Barcelona, Spain

    Andreas Kaltenbrunner

Authors
  1. Francesco Bonchi
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  2. Francesco Gullo
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  3. Andreas Kaltenbrunner
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Corresponding author

Correspondence to Francesco Bonchi .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Reda Alhajj

  2. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Jon Rokne

Section Editor information

  1. Arizona State University, Tempe, AZ, USA

    Huan Liu

  2. Chief Data Scientist, Clari Inc., 94086, Sunnyvale, CA, USA

    Lei Tang

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Bonchi, F., Gullo, F., Kaltenbrunner, A. (2018). Core Decomposition of Massive, Information-Rich Graphs. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_110176

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