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research article

Towards Unbiased BFS Sampling

Kurant, Maciej
•
Markopoulou, Athina
•
Thiran, Patrick  
2011
IEEE Journal on Selected Areas in Communications

Breadth First Search (BFS) is a widely used approach for sampling large graphs. However, it has been empirically observed that BFS sampling is biased toward high-degree nodes, which may strongly affect the measurement results. In this paper, we quantify and correct the degree bias of BFS.

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Type
research article
DOI
10.1109/JSAC.2011.111005
Web of Science ID

WOS:000295341600005

Author(s)
Kurant, Maciej
Markopoulou, Athina
Thiran, Patrick  
Date Issued

2011

Publisher

Institute of Electrical and Electronics Engineers

Published in
IEEE Journal on Selected Areas in Communications
Volume

29

Start page

1799

End page

1809

Subjects

Breadth-First-Search (BFS)

•

network topology

•

sampling methods

•

bias

•

estimation

•

online social networks

•

Hidden Populations

•

Finite Population

•

Degree Sequence

•

Replacement

•

Networks

•

Probabilities

•

Graphs

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
INDY2  
Available on Infoscience
December 16, 2011
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/73513
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