Data sources

[NMerz]

A suggestion of a variety of sparse graphs from different domains: Associated medical terms: https://sparse.tamu.edu/Sybrandt/AGATHA_2015 Road: https://networkrepository.com/road-usa.php RGG (random, social-network-esq): https://sparse.tamu.edu/DIMACS10/rgg_n_2_23_s0 Amazon book recommendations: https://networkrepository.com/rec-amz-Books.php Twitter social graph: https://networkrepository.com/soc-twitter.php UK web 2005: https://networkrepository.com/web-uk-2005-all.php Patent citations: https://snap.stanford.edu/data/cit-Patents.html "Delaunay triangulations of random points in the unit square": https://sparse.tamu.edu/DIMACS10/delaunay_n23 soc-ljournal-2008: https://networkrepository.com/soc-ljournal-2008.php

[NMerz]

Questions:

• Can a reasonable argument be made for using pagerank in these domains? -- Is there another closely adjacent algorithm which may make sense?
• does this fully satisfy the "wide range of sparse graphs" that makes the project interesting? (It extends well beyond the traditional social/web graphs uses here)

[pandeyshubham25]

1) Absolutely, I found an awesome summary of several applications here (indexed at page 330 in this pdf, work by one of the profs at Purdue.)- https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202015%20-%20prbeyond.pdf . 2) All of these have to be sparse, I am only doubtful on 'wide range'