Alignment Heuristics
Alignment Heuristics is a computational strategy within network alignment that employs approximate, often greedy, methods to efficiently identify node correspondences across networks by prioritizing local topological or attribute similarities, distinguishing itself from exact or globally optimal approaches through its focus on scalability and practical tractability in large-scale or complex network scenarios.
24
Publications
1.1K
Citations
81
Authors
44
Institutions
Publications per year
2017–2026
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44
Mississippi State University
Starkville, United States
2 h-index
4 publications
122 citations
University of Vienna
Vienna, Austria
1 h-index
1 publications
25 citations
Fraunhofer Institute for Cell Therapy and Immunology
Leipzig, Germany
1 h-index
1 publications
25 citations
Leipzig University
Leipzig, Germany
1 h-index
3 publications
75 citations

University of Alberta
Edmonton, Canada
1 h-index
4 publications
96 citations
University of Florida
Gainesville, United States
1 h-index
3 publications
45 citations
Kyushu University
Fukuoka, Japan
1 h-index
2 publications
40 citations
Universidade Federal de Minas Gerais
Belo Horizonte, Brazil
1 h-index
3 publications
54 citations
1–8 of 44
2 publications · 45 citations
2
h-index
1 publications · 17 citations
1
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1 publications · 111 citations
1
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1 publications · 118 citations
1
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BPMJ · 1 publications · 26 citations
1
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1–5