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Community detection, link prediction, and layer interdependence in multilayer networks. "Complex systems are often characterized
Community detection, link prediction, and layer interdependence in multilayer networks.
"Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure."
This paper describes a new algorithm to model multi-layered complex
networks with an example of social support structures in an Indian
village.
Classifying and analysing learning environments is feasible with this type of modelling but would rely heavily on the technical support of analysts familiar with complex systems.
Source: journals.aps.org
layer multilayer complex layers model prediction communities structure
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