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This work studies a central extremal graph theory problem inspired by a 1975 conjecture of Erd\H{o}s, which aims to find graphs with a given size (number of nodes) that maximize the number of edges without having 3- or 4-cycles.
Vraagstuk xxviii
Willem Mantel · 1907
Earlier work this paper cites.
On an extremal problem in graph theory
Pál Turán · 1941
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On a problem of graph theory
Paul Erdős, Alfréd Rényi, and Vera T. Sós · 1966
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