Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP240101108]Researchers: Professor Hongzhi Yin (Chief Investigator) , Quoc Viet Hung Nguyen (Chief Investigator)
Brief description Privacy-Aware and Personalised Explanation Overlays for Recommender Systems. AI-powered recommender systems provide recommendations for daily lives, but they need to be legally interpretable and explainable. This project aims to transform existing black-box recommender models into transparent and trustworthy decision-support systems. The resulting tools will offer granular, explorable rationales for the recommendations in real time, creating greater public confidence while advancing the field. The expected outcomes include graph embedding methods for capturing real-world relationships in all their messiness and complexity. The anticipated contributions include impartial and accountable recommender models that are resistant to adversarial attacks and that slow the spread of misinformation.
Funding Amount $376,482
Funding Scheme Discovery Projects
- PURL : https://purl.org/au-research/grants/arc/DP240101108
- ARC : DP240101108