A Reliable Knowledge Discovery System on Dynamic Academic Graphs. This project develops a reliable knowledge discovery system that analyses dynamic academic data to reveal novel knowledge insights, fo

Description

A Reliable Knowledge Discovery System on Dynamic Academic Graphs. This project develops a reliable knowledge discovery system that analyses dynamic academic data to reveal novel knowledge insights, for example, predicting emerging research topics, novel gene-disease associations, and impactful scientific collaborations. By advancing these techniques, the system focuses on underrepresented knowledge of less frequent but emerging data patterns and instantly detects anomalies that indicate novel or noisy data. Expected outcomes are a hierarchical graph representation model, a robust anomaly detection framework, and a dynamic knowledge discovery system to provide reliable predictive results. Benefits include early access to reliable predictions, supporting informed policymaking and strategic management.. Scheme: Discovery Early Career Researcher Award. Field: 4610 - Library and Information Studies. Lead: Dr Mengjia Wu