Discovery Projects - Grant ID: DP220102635

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP220102635

Funding Status
Active

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Funded Activity Summary

Robust meta learning for risk-aware recommender systems. Recommender systems are the core of many online services but they are highly vulnerable to risks like shilling attacks, privacy leaks, and unexpected change. This project aims to develop new adversarial Bayesian-based, privacy-preserved and self-adaptive fuzzy meta learning methods and meta recommender systems that are robust to these risky, uncertain and dynamic environments. The anticipated outcomes should significantly improve the reliability of recommender systems with particular benefits for online personalised service systems, e.g., e-government, e-business and e-Learning. The outcomes will also advance machine learning knowledge with a new robust meta learning schema for general data analytics and applications.

Funded Activity Details

Start Date: 03-10-2022

End Date: 02-10-2025

Funding Scheme: Discovery Projects

Funding Amount: $494,500.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Neural, Evolutionary and Fuzzy Computation | Pattern Recognition and Data Mining | Decision Support and Group Support Systems | Artificial Intelligence and Image Processing

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Information and Computing Sciences | Application Software Packages (excl. Computer Games) | Information Processing Services (incl. Data Entry and Capture) |

Other Keywords

Application Software Packages (excl. Computer Games) | Artificial Intelligence and Image Processing | Decision Support and Group Support Systems | Expanding Knowledge in the Information and Computing Sciences | Information Processing Services (incl. Data Entry and Capture) | Neural, Evolutionary and Fuzzy Computation | Pattern Recognition and Data Mining

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