Prepare

Download the 4 first files from http://cfinder.org/wiki/?n=Main.Data#toc1
Extract the files into folder /data.

pagerank.py: in the form of pseudo code

This program shows the result of page rank of graph in file dirLinks.txt with name-node mapping in "pageNum2Name.txt".
Run this program with alpha value (damping factor) as argument:
python3 pagerank.py <alpha-value>. The alpha value recommended is 0.15.

pagerank_highPerformance.py: represent the matrix by an array

This program will run the algorithm of page rank on graph in file data/alr21--dirLinks--enwiki-20071018.txt with name-node mapping in data/alr21--pageNum2Name--enwiki-20071018.txt.
Run this program with alpha value (damping factor) as argument:
python3 pagerank_highPerformance.py <alpha-value>. The alpha value recommended is 0.15.

pagerank_personalized.py: with a personnalized interesting vector

Search the category in which you are interested in the file data/alr21--categNum2Name--enwiki-20071018.txt. For exemple the cateogry "Chess" has ID of 691713 and the category "Boxing" has ID of 738624.
Run python3 pagerank_personalized.py <alpha-value> 691713 738624 to have a page rank related to these 2 categories.

pagerank_push.py: use push method to run personalized page rank

Same usage with pagerank_personalized.py but implemented with "push" method of algorithm Page Rank. Read: http://www.math.ucsd.edu/~fan/wp/localpartition.pdf