Non-backtracking cycles: length spectrum theory and graph mining applications

Non-backtracking cycles: length spectrum theory and graph mining applications

Abstract Graph distance and graph embedding are two fundamental tasks in graph mining. For graph distance, determining the structural dissimilarity between networks is an ill-defined problem, as there is no canonical way to compare two networks. Indeed, many of the existing approaches for network co...

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Bibliografiske detaljer
Main Authors: Leo Torres, Pablo Suárez-Serrato, Tina Eliassi-Rad
Format: Article
Sprog:English
Udgivet: SpringerOpen 2019-06-01
Serier:Applied Network Science
Fag:
Graph distance
Graph embedding
Algebraic topology
Length spectrum
Online adgang:http://link.springer.com/article/10.1007/s41109-019-0147-y

Internet

http://link.springer.com/article/10.1007/s41109-019-0147-y

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