Sampling as a Method of Comparing Real and Generated Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10238665" target="_blank" >RIV/61989100:27240/18:10238665 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-319-68527-4_13" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-68527-4_13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-68527-4_13" target="_blank" >10.1007/978-3-319-68527-4_13</a>

Result language

angličtina

Original language name

Sampling as a Method of Comparing Real and Generated Networks

Original language description

In this paper, we combine the use of sampling methods and a network generator to assess the degree of similarity between real and generated networks. Generative network models provide a tool for studying essential network features. These include, for example, the average and distribution of node degree, cluster coefficient and community size. The aim of the generators based on these models is to create networks with properties close to real networks. Even with a high similarity of global properties of real and generated networks, the local structures of these networks often differ considerably. On the other hand, when the network is reduced by a sampling method, global features of networks are strongly influenced by local structures. In the paper, we compare properties of a real-world network and a generated network and also properties of their small samples. In experiments, we show how the distribution of the properties of individual networks change by using different sampling methods and how these distributions differ for both networks and their small samples. (C) 2018, Springer International Publishing AG.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Advances in Intelligent Systems and Computing. Volume 682

ISBN

978-3-319-68526-7

ISSN

2194-5357

e-ISSN

neuvedeno

Number of pages

11

Pages from-to

117-127

Publisher name

Springer Verlag

Place of publication

Cham

Event location

Málaga

Event date

Oct 9, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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