Abstract
Finding outliers in networks is a central task in different application domains. Here, we exploit the stochastic block model framework to study the network from a generative point of view and design a score able to highlight those nodes whose connection with the rest of the network violates in some way the law according to which the rest of the nodes are interconnected. The peculiarity of our approach is that no pre-defined notion of outlier is employed; rather outliers emerge as deviations from the underlying network generating mechanism.
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Angiulli, F., Fassetti, F., Serrao, C. (2021). A Stochastic Block Model Based Approach to Detect Outliers in Networks. In: Strauss, C., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2021. Lecture Notes in Computer Science(), vol 12923. Springer, Cham. https://doi.org/10.1007/978-3-030-86472-9_14
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DOI: https://doi.org/10.1007/978-3-030-86472-9_14
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