Cited By
View all- Yang SZhu WZhang KDiao YBai Y(2024)Influence Maximization in Temporal Social Networks with the Mixed K-Shell MethodElectronics10.3390/electronics1313253313:13(2533)Online publication date: 27-Jun-2024
Closeness Centrality on Uncertain Graphs
Article No.: 29, Pages 1 - 29
Abstract
Centrality is a family of metrics for characterizing the importance of a vertex in a graph. Although a large number of centrality metrics have been proposed, a majority of them ignores uncertainty in graph data. In this article, we formulate closeness centrality on uncertain graphs and define the batch closeness centrality evaluation problem that computes the closeness centrality of a subset of vertices in an uncertain graph. We develop three algorithms, MS-BCC, MG-BCC, and MGMS-BCC, based on sampling to approximate the closeness centrality of the specified vertices. All these algorithms require to perform breadth-first searches (BFS) starting from the specified vertices on a large number of sampled possible worlds of the uncertain graph. To improve the efficiency of the algorithms, we exploit operation-level parallelism of the BFS traversals and simultaneously execute the shared sequences of operations in the breadth-first searches. Parallelization is realized at different levels in these algorithms. The experimental results show that the proposed algorithms can efficiently and accurately approximate the closeness centrality of the given vertices. MGMS-BCC is faster than both MS-BCC and MG-BCC because it avoids more repeated executions of the shared operation sequences in the BFS traversals.
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Index Terms
- Closeness Centrality on Uncertain Graphs
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Publication History
Published: 11 July 2023
Online AM: 15 June 2023
Accepted: 20 May 2023
Revised: 08 March 2023
Received: 17 May 2022
Published in TWEB Volume 17, Issue 4
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- National Natural Science Foundation of China
- Open Research Projects of Zhejiang Lab
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View all- Yang SZhu WZhang KDiao YBai Y(2024)Influence Maximization in Temporal Social Networks with the Mixed K-Shell MethodElectronics10.3390/electronics1313253313:13(2533)Online publication date: 27-Jun-2024
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