A big graph clustering method to support parallel processing by perceiving graph’s application algorithm semantics

As the size of graph data grows exponentially, it is usually processed by parallel and distributed computing environment. During parallel processing, the first step is to divide the graph data into many subgraphs and then place them on different computational nodes. However, the existing graph clust...

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Vydané v:	The Journal of supercomputing Ročník 80; číslo 2; s. 2838 - 2861
Hlavní autori:	Cheng, Tengteng, Zeng, Guosun, Sun, Zhipeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.01.2024 Springer Nature B.V
Predmet:	Algorithms Clustering Communication Compilers Computer Science Distributed processing Graph theory Interpreters Methods Modularity Parallel processing Processor Architectures Programming Languages Semantics Social networks Graph clustering Parallel processing Semantic serial degree Big graph Modularity of a subgraph Graph’s application algorithm
ISSN:	0920-8542, 1573-0484
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