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A Block-Based Edge Partitioning for Random Walks ...
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由 Y Li 著作2016被引用 4 次 — Recent results [5, 9, 23] prove that edge partitioning approaches (also known as vertex-cut) outperform vertex partitioning (edge-cut) ...
A Block-Based Edge Partitioning for Random Walks ...
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由 Y Li 著作2016被引用 4 次 — a block-based partitioning strategy which considers graph algorithms specificities and the topological prop- erties of real-world large graphs ...
A Block-Based Edge Partitioning for Random Walks ...
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We propose in this paper a vertex-cut partitioning dedicated to random walks algorithms which takes advantage of graph topological properties. It relies on a ...
A block-based edge-partitionning for random walks ...
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Our experiments illustrate the benefit of our partitioning since it significantly reduce the communication cost when performing random walks-based algorithms ...
A Block-Based Edge Partitioning for Random Walks ...
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We propose in this paper a vertex-cut partitioning dedicated to random walks algorithms which takes advantage of graph topological properties. It relies on a ...
A Block-Based Edge Partitioning for Random Walks Algorithms ...
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Yifan Li, Camélia Constantin, Cédric du Mouza: A Block-Based Edge Partitioning for Random Walks Algorithms over Large Social Graphs. WISE (2) 2016: 275-289.
A block-based edge-partitionning for random walks ...
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2024年12月16日 — Recent results [5, 9, 23] prove that edge partitioning approaches (also known as vertex-cut) outperform vertex partitioning (edge-cut) ...
[LCd16] A Block-Based Edge Partitioning for Random Walks ...
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[LCd16] A Block-Based Edge Partitioning for Random Walks Algorithms over Large Social Graphs ... motcle: Résumé: Recent results prove that edge partitioning ...
Block Exchange in Graph Partitioning
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由 WW Hager 著作2000被引用 14 次 — In their algorithm, a vertex from one set in the current partition is exchanged with a vertex in the other set to reduce the sum of the weights of cut edges.
A Label-based Edge Partitioning for Multi-Layer Graphs
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Social network systems rely on very large underlying graphs. Consequently, to achieve scalability, most data analytics and data mining algorithms are ...