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Content Provider | ACM Digital Library |
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Author | Li, Xing Chen, Zhuo Deng, Beixing Chen, Yang Ding, Cong |
Abstract | Computing the shortest-path distances between nodes is a key problem in analyzing social graphs. Traditional methods like breadth-first search (BFS) do not scale well with graph size. Recently, a Graph Coordinate System, called Orion, has been proposed to estimate shortest-path distances in a scalable way. Orion uses a landmark-based approach, which does not take account of the shortest-path distances between non-landmark nodes in coordinate calculation. Such biased input for the coordinate system cannot characterize the graph structure well. In this paper, we propose Pomelo, which calculates the graph coordinates in a decentralized manner. Every node in Pomelo computes its shortest-path distances to both nearby neighbors and some random distant neighbors. By introducing the novel partial BFS, the computational overhead of Pomelo is tunable. Our experimental results from different representative social graphs show that Pomelo greatly outperforms Orion in estimation accuracy while maintaining the same computational overhead. |
Starting Page | 406 |
Ending Page | 407 |
Page Count | 2 |
File Format | |
ISBN | 9781450307970 |
DOI | 10.1145/2018436.2018491 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2011-08-15 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Graph coordinate system Online social network |
Content Type | Text |
Resource Type | Article |
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