SAGA: Signal-Aware Graph Aggregation

McNeil, Maxwell; Ma, Boya; Bogdanov, Petko

doi:10.1137/1.9781611977172.16

Cited by 3 publications

(3 citation statements)

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“…It labels the query as abnormal if its spectrum is far from the expected values. CADENCE [11] uses past interactions to identify community structures that are stable over time. It labels a query as abnormal if it implies a community reconfiguration.…”

Section: Related Workmentioning

confidence: 99%

“…queries, like time-stamped nodes [6,7] or entire graph snapshots [8][9][10][11], have also been proposed. These algorithms also vary in the way they define an anomaly and use the context.…”

Section: Introductionmentioning

confidence: 99%

“…These algorithms also vary in the way they define an anomaly and use the context. Namely, nodes may be deemed abnormal if they suddenly change their centrality [6] or communication counts [7], while graphs may be considered abnormal if they have sudden densifications [9], spectrum changes [10], or community re-configurations [11], to list some examples.…”

Section: Introductionmentioning

confidence: 99%

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MAD: Multi-Scale Anomaly Detection in Link Streams

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et al. 2024

Proceedings of the 17th ACM International Conference on Web Search and Data Mining

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Section: Related Workmentioning

confidence: 99%

“…queries, like time-stamped nodes [6,7] or entire graph snapshots [8][9][10][11], have also been proposed. These algorithms also vary in the way they define an anomaly and use the context.…”

Section: Introductionmentioning

confidence: 99%