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- W4384698903 abstract "Discovering dense substructures in graphs is a fundamental topic in graph mining, and has been studied across many areas including computational biology, spam and fraud-detection, and large-scale network analysis. Recently, Sariyuce et al. introduced the nucleus decomposition problem, which generalizes the influential notions of k-cores and k-trusses to k-(r,s) nucleii, and can better capture higher-order structures. Informally, a k-(r,s) nucleus is the maximal induced subgraph such that every r-clique in the subgraph is contained in at least k s-cliques. The goal of the (r, s) nucleus decomposition problem is to identify for each r-clique in the graph, the largest k such that it is in a k-(r,s) nucleus." @default.
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- W4384698903 date "2023-07-18" @default.
- W4384698903 modified "2023-09-23" @default.
- W4384698903 title "Theoretically and Practically Efficient Parallel Nucleus Decomposition (Abstract)" @default.
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- W4384698903 doi "https://doi.org/10.1145/3597635.3598024" @default.
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