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
5,248 citations
3,888 citations
"Graph based anomaly detection and d..." refers methods in this paper
...The research directions in this category include: algebraic connectivity [Fiedler, 1973] [Wilson and Zhu, 2008]), a spectral method that has been studied thoroughly; an SVM-based approach on global feature vectors [Li et al., 2011a]; social networks similarity [Macindoe and Richards, 2010] which is…...
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...The research directions in this category include: algebraic connectivity (Fiedler 1973; Wilson and Zhu 2008), a spectral method that has been studied thoroughly; an SVM-based approach on global feature vectors (Li et al....
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3,386 citations
"Graph based anomaly detection and d..." refers background in this paper
...The slightly more complex Katz measure Katz [1953] counts all the paths weighted inversely proportional to the path length....
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3,314 citations