pygrank: A Python Package for Graph Node Ranking
Machine Learning
2021-10-19 v1
Abstract
We introduce pygrank, an open source Python package to define, run and evaluate node ranking algorithms. We provide object-oriented and extensively unit-tested algorithm components, such as graph filters, post-processors, measures, benchmarks and online tuning. Computations can be delegated to numpy, tensorflow or pytorch backends and fit in back-propagation pipelines. Classes can be combined to define interoperable complex algorithms. Within the context of this paper we compare the package with related alternatives and demonstrate its flexibility and ease of use with code examples.
Keywords
Cite
@article{arxiv.2110.09274,
title = {pygrank: A Python Package for Graph Node Ranking},
author = {Emmanouil Krasanakis and Symeon Papadopoulos and Ioannis Kompatsiaris and Andreas Symeonidis},
journal= {arXiv preprint arXiv:2110.09274},
year = {2021}
}
Comments
6 pages, 1 figure, 2 tables, 3 code snippets