Data clustering with edge domination in complex networks
Social and Information Networks
2017-05-17 v1 Machine Learning
Physics and Society
Abstract
This paper presents a model for a dynamical system where particles dominate edges in a complex network. The proposed dynamical system is then extended to an application on the problem of community detection and data clustering. In the case of the data clustering problem, 6 different techniques were simulated on 10 different datasets in order to compare with the proposed technique. The results show that the proposed algorithm performs well when prior knowledge of the number of clusters is known to the algorithm.
Cite
@article{arxiv.1705.05494,
title = {Data clustering with edge domination in complex networks},
author = {Paulo Roberto Urio and Zhao Liang},
journal= {arXiv preprint arXiv:1705.05494},
year = {2017}
}
Comments
13 pages, 6 figures