March 22, 2024, 4:42 a.m. | Kirill Lukyanov, Mikhail Drobyshevskiy, Danil Shaikhelislamov, Denis Turdakov

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.13865v1 Announce Type: cross
Abstract: Social networks crawling is in the focus of active research the last years. One of the challenging task is to collect target nodes in an initially unknown graph given a budget of crawling steps. Predicting a node property based on its partially known neighbourhood is at the heart of a successful crawler. In this paper we adopt graph neural networks for this purpose and show they are competitive to traditional classifiers and are better for …

abstract arxiv budget crawling cs.lg cs.si focus graph graph neural network network networks neural network node nodes property research social social networks type

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