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Grant Award View - GA64734-V1
Searching Cohesive Subgraphs in Big Attributed Graph Data
GA ID:
GA64734-V1
Agency:
Australian Research Council
Approval Date:
4-Dec-2019
Variation Publish Date:
2-Aug-2021
Variation Date:
27-Jul-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2020 to 31-Dec-2022
Value (AUD):
$495,000.00
(GST inclusive where applicable)
Varies:
GA64734
- Searching Cohesive Subgraphs in Big Attributed Graph Data
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Searching Cohesive Subgraphs in Big Attributed Graph Data
Purpose:
The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation.
GO ID:
GO Title:
Discovery Projects for funding commencing in 2020
Internal Reference ID:
DP20 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
Swinburne University of Technology
Recipient ABN:
13 628 586 699
Grant Recipient Location
Suburb:
HAWTHORN
Town/City:
HAWTHORN
Postcode:
3122
State/Territory:
VIC
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
VIC
Postcode:
3122
Country:
AUSTRALIA