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README
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© 2017 KAUST - InfoCloud group
Ziyad Al-Ghamdi <Ziyad.AlGhamdi@kaust.edu.sa>
Fuad Jamour <fuad.jamour@kaust.edu.sa>
=============================================
BeBeCA
=============================================
This readme file contains information about using the contents of this framework
to build and test your betweenness centrality approximation algorithms.
----------------------------------------------
- Contents -
----------------------------------------------
Included in this release are the following files and directories:
- README This document
- Evaluation_Methodology/ Contains all evaluation scripts, the graphs and
the exact betweenness centrality scores that is
used for evaluating betwenness centraity approximation
algorithms.
- Source_Code/ Contains the source coude for several approxiamtion
algorithms presented in the paper.
----------------------------------------------
- Getting started -
----------------------------------------------
All the required scripts, graph inputs and the exact betweenness centrality
scores are available in the directory Evaluation_Methodology/ and all you have
to do is to run the script Evaluation_Methodology/BeBeCA.sh to get the following
evaluation metrics:
1- Average Error
2- Maximum Error
3- Top 1% Hit
4- Kindall-tau Distance
Evaluation_Methodology/BeBeCA.sh takes as arguments:
1- The exact betweenness centrality scores file path.
2- The approximate betweenness centrality scores file path.
3- The output file name that will contain the evaluation metrics.
For further details about the evaluation framework, please read
Evaluation_Methodology/README.txt
All of our approxiamtion algorithms implmentations are available in the directory
Source_Code/ along with the way to compile them.
For further details about how to compile and run each of the algorithms, please read
Source_Code/README.txt