Name
Title | ||
|---|---|---|
Scalable Processing of Massive Uncertain Graph Data: A Simultaneous Processing Approach |
Abstract | ||
|---|---|---|
This paper studies a novel approach to processing massive uncertain graph data. In this approach, we propose a new framework to simultaneously process a query on a set of randomly sampled possible worlds of an uncertain graph. Based on this framework, we develop a series of algorithms to analyze massive uncertain graphs, including breadth-first search, shortest distance queries, triangle counting, and core decomposition. We implement this approach based on GraphLab, one of the stateof-the-art graph processing frameworks. By sharing fine-grained internal processing steps on common substructures of sampled possible worlds, the new approach achieves tens to hundreds of times speedup in execution time on a cluster of 20 servers. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICDE.2017.70 | 2017 IEEE 33rd International Conference on Data Engineering (ICDE) |
Keywords | Field | DocType |
scalable processing,massive uncertain graph data,query processing,breadth-first search,shortest distance queries,triangle counting,core decomposition,GraphLab,graph processing | Data structure,Data mining,Computer science,Server,AC power,Theoretical computer science,Sampling (statistics),Probabilistic logic,Database,Scalability,Speedup,Possible world | Conference |
ISSN | ISBN | Citations |
1084-4627 | 978-1-5090-6544-8 | 1 |
PageRank | References | Authors |
0.35 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhaonian Zou | 1 | 331 | 15.78 |
| Faming Li | 2 | 1 | 0.35 |
| Jianzhong Li | 3 | 63 | 24.23 |
| Yingshu Li | 4 | 671 | 53.71 |