IJCAI 2021poster5 citations
An Axiom System for Feedback Centralities
Abstract
In recent years, the axiomatic approach to centrality measures has attracted attention in the literature. However, most papers propose a collection of axioms dedicated to one or two considered centrality measures. In result, it is hard to capture the differences and similarities between various measures. In this paper, we propose an axiom system for four classic feedback centralities: Eigenvector centrality, Katz centrality, Katz prestige and PageRank. We prove that each of these four centrality measures can be uniquely characterized with a subset of our axioms. Our system is the first one in the literature that considers all four feedback centralities.
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BibTeX
@inproceedings{ijcai2021p62,
title = {An Axiom System for Feedback Centralities},
author = {Wąs, Tomasz and Skibski, Oskar},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {443--449},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/62},
url = {https://doi.org/10.24963/ijcai.2021/62},
}