The goal of the PAGA project is to design, implement and evaluate parallel algorithms for large-scale graph analysis. In particular, we are interested in scalable approaches for computing centrality metrics on distributed memory architectures. Centrality metrics such as betweenness centrality, clustering coefficient, closeness centrality and others, are widely used in social network analysis.
Moreno Marzolla (2013). PAGA (Parallel Algorithms for Graph Analysis)..
PAGA (Parallel Algorithms for Graph Analysis).
MARZOLLA, MORENO
2013
Abstract
The goal of the PAGA project is to design, implement and evaluate parallel algorithms for large-scale graph analysis. In particular, we are interested in scalable approaches for computing centrality metrics on distributed memory architectures. Centrality metrics such as betweenness centrality, clustering coefficient, closeness centrality and others, are widely used in social network analysis.File in questo prodotto:
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