Learning attribute and homophily measures through random walks

Learning attribute and homophily measures through random walks

Abstract We investigate the statistical learning of nodal attribute functionals in homophily networks using random walks. Attributes can be discrete or continuous. A generalization of various existing canonical models, based on preferential attachment is studied (model class $$\mathscr {P}$$ P ), wh...

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Bibliographic Details
Main Authors: Nelson Antunes, Sayan Banerjee, Shankar Bhamidi, Vladas Pipiras
Format: Article
Language:English
Published: SpringerOpen 2023-06-01
Series:Applied Network Science
Subjects:
Attributed networks
Homophily
Network model
Resolvability
Random walk samplings
Discrete and continuous attributes
Online Access:https://doi.org/10.1007/s41109-023-00558-3

Internet

https://doi.org/10.1007/s41109-023-00558-3

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