Fast Anomaly Detection in Graphs [pdf]
The NUS School of Computing is recognised among the top global universities for computer science; and exemplifies academic excellence and innovative research.
Fast Anomaly Detection in Graphs [pdf] launched on April 7, 2020 with 215 votes, #122 of 5,003 launches that month and more than 95% of that year's launches. The site was not reachable when checked in September 2026.
In plain words
Fast Anomaly Detection in Graphs is a research tool designed to identify unusual patterns and outliers in graph-structured data. It is built for researchers and data scientists who work with network analysis and need to detect anomalies quickly. The tool emphasizes speed and efficiency in processing large graph datasets to flag suspicious or unexpected connections and behaviors.
written from the facts on this page · September 2026
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