Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP140100104]Researchers: A/Prof Xue Li (Chief Investigator) , Michael Sheng (Chief Investigator) , Associate Professor Robert Boots (Partner Investigator) , Prof Jeffrey Lipman (Partner Investigator)
Brief description Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.
Funding Amount $411,000
Funding Scheme Discovery Projects
- PURL : https://purl.org/au-research/grants/arc/DP140100104
- ARC : DP140100104