Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

Matthias Dehmer; Frank Emmert-Streib

doi:10.1016/j.amc.2007.04.006

Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

Matthias Dehmer^*
, Frank Emmert-Streib

^*Corresponding author for this work

Max F. Perutz Laboratories
University of Vienna
Medical University of Vienna
University of Veterinary Medicine Vienna
Stowers Institute for Medical Research

Research output: Contribution to journal › Article › peer-review

Abstract

In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity.

Original language	English
Pages (from-to)	7-20
Number of pages	14
Journal	Applied Mathematics and Computation
Volume	194
Issue number	1
DOIs	https://doi.org/10.1016/j.amc.2007.04.006
Publication status	Published - 1 Dec 2007
Externally published	Yes

Keywords

Complexity analysis
Graph classes
Graph classification
Graph similarity
Hierarchical models
Structured objects

Access to Document

10.1016/j.amc.2007.04.006

Cite this

@article{14da6653af8344c0a68cc86a9657b37a,

title = "Structural similarity of directed universal hierarchical graphs: A low computational complexity approach",

abstract = "In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity.",

keywords = "Complexity analysis, Graph classes, Graph classification, Graph similarity, Hierarchical models, Structured objects",

author = "Matthias Dehmer and Frank Emmert-Streib",

year = "2007",

month = dec,

day = "1",

doi = "10.1016/j.amc.2007.04.006",

language = "English",

volume = "194",

pages = "7--20",

journal = "Applied Mathematics and Computation",

issn = "0096-3003",

publisher = "Elsevier Inc.",

number = "1",

}

TY - JOUR

T1 - Structural similarity of directed universal hierarchical graphs

T2 - A low computational complexity approach

AU - Dehmer, Matthias

AU - Emmert-Streib, Frank

PY - 2007/12/1

Y1 - 2007/12/1

N2 - In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity.

AB - In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity.

KW - Complexity analysis

KW - Graph classes

KW - Graph classification

KW - Graph similarity

KW - Hierarchical models

KW - Structured objects

UR - https://www.scopus.com/pages/publications/35648968162

U2 - 10.1016/j.amc.2007.04.006

DO - 10.1016/j.amc.2007.04.006

M3 - Article

AN - SCOPUS:35648968162

SN - 0096-3003

VL - 194

SP - 7

EP - 20

JO - Applied Mathematics and Computation

JF - Applied Mathematics and Computation

IS - 1

ER -

Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this