Statistical inference on attributed random graphs: Fusion of graph features and content: An experiment on time series of Enron graphs

Carey E. Priebe, Youngser Park, David J. Marchette, John M. Conroy, John Grothendieck and Allen L. Gorin

Computational Statistics & Data Analysis, 2010, vol. 54, issue 7, 1766-1776

Abstract: Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph feature-only statistics. In this paper, we design and execute an experiment on a time series of attributed graphs extracted from the Enron email corpus which demonstrates the benefit of fusion. The experiment is based on injecting a controlled anomaly into the real data and measuring its detectability.

Keywords: Time; series; analysis; Clustering; Metadata; Feature; representation; Statistical; methods; Graph; theory (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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