Graph based anomaly detection and description: a survey
Citations
915 citations
Cites methods from "Graph based anomaly detection and d..."
...In particular, for many of the methods applied in the works discussed above – such as outlier detection or association rule mining – graph-based variants have been proposed in the literature [2,43]....
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777 citations
737 citations
Cites methods from "Graph based anomaly detection and d..."
...This also holds true in anomaly detection and there exist many algorithms for detecting anomalies in graphs [30], in sequences and time series [31] and for addressing spatial data [32]....
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562 citations
Cites background from "Graph based anomaly detection and d..."
...Graphs naturally arise in many real-world applications, including social analysis [1], fraud detection [2, 3], traffic prediction [4], computer vision [5], and many more....
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560 citations
References
3,192 citations
"Graph based anomaly detection and d..." refers background or methods in this paper
...We also include other discretization techniques that could apply under this setting such as SAX [Lin et al., 2003], MDL-binning [Kontkanen and Myllymki, 2007], and minimum entropy discretization [Fayyad and Irani, 1993]....
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..., 2003], MDL-binning [Kontkanen and Myllymki, 2007], and minimum entropy discretization [Fayyad and Irani, 1993]....
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2,937 citations
"Graph based anomaly detection and d..." refers background or methods in this paper
...Relational classification methods can be categorized into local and global methods [Sen et al., 2008]....
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...Relational classification methods can be categorized into local and global methods (Sen et al. 2008)....
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2,548 citations
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2,180 citations