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GraphAn: Graph-based Subsequence Anomaly Detection

Summary: GraphAn: graph-based system for subsequence anomaly detection on Series2Graph, using low-dimensional embeddings. Unsupervised detection of single and recurrent anomalies without prior knowledge, with accuracy and fast performance on large datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12170
Venue
VLDB
Year
2020
Pagerank
5.2039218e-05
Overall Rank
6,116 | 57.46%
DOI
10.14778/3415478.3415514

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
161 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00039846974
2,629 Online Outlier Detection in Sensor Data Using Non-Parametric Models 2006 VLDB 8.4160309e-05
2,644 Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series 2020 VLDB 8.3832357e-05
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