DocumentCode :
1797354
Title :
A credible property of resistance distance on real-world networks
Author :
Yun-Yan Xiong ; Dong Han ; Yi-Jun Mao
Author_Institution :
Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
1
fYear :
2014
fDate :
13-16 July 2014
Firstpage :
94
Lastpage :
97
Abstract :
On the basis of introducing the development of resistance distance, an important property of resistance distance was discussed. That is, Vertices in the same cluster of a graph have a small commute distance, whereas two vertices in different clusters of a graph have a “large” commute distance. The credible property was proved to be flawed on random geometric graphs by a research team. For the corrections of resistance distance mentioned by the research team, some experiments were made on real-world network data sets instead. The experiments showed that the property did not hold on rather small real-world network. Moreover, the computation results showed that the correction by von Luxburg did better than the correction by Brand.
Keywords :
geometry; graph theory; network theory (graphs); commute distance; credible property; graph clusters; graph vertices; random geometric graphs; real-world networks; resistance distance; Abstracts; Chemistry; Dolphins; Europe; Community; Laplacian matrix; Resistance distance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
ISSN :
2160-133X
Print_ISBN :
978-1-4799-4216-9
Type :
conf
DOI :
10.1109/ICMLC.2014.7009098
Filename :
7009098
Link To Document :
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