© 2017 KAUST - InfoCloud group
Ziyad Al-Ghamdi  <Ziyad.AlGhamdi@kaust.edu.sa>
Fuad Jamour <fuad.jamour@kaust.edu.sa>

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BeBeCA

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This readme file contains information about using the contents of this framework
to build and test your betweenness centrality approximation algorithms.

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-                  Contents                  -
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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. 
                                  
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-               Getting started              -
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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