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Oct 7, 2023 · Abstract:Finding dense subgraphs of a large network is a fundamental problem in graph mining that has been studied extensively both for its ...
Feb 21, 2024 · The multiplex p-mean density objective uses parameter to model the trade-off between high density and the cumulative importance of layers ...
Finding dense subgraphs of a large network is a fundamental problem in graph mining that has been studied extensively both for its theoretical richness and its ...
Feb 23, 2024 · Existing dense subgraph mining methods in multiplex graphs consider the same importance for different types of connections, while in real-world ...
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Oct 7, 2023 · Finding dense subgraphs of a large network is a fundamental problem in graph mining that has been studied extensively both for its ...
While the problem of finding the densest subgraph in simple graphs is a well-studied problem [42], finding dense subgraphs from multiplex networks recently ...
Among many network analysis techniques, dense subgraph discovery, aiming to find a dense component in a network, is an essential primitive with a variety of ...
We apply our multilayer core-decomposition tool to solve both our general formulation of multilayer densest subgraph and the spe- cific densest-common-subgraph ...
In this paper, in general, we are not searching for in- duced subgraphs: we do not require equal number of edges to exist between nodes in the template and ...
To solve the densest subgraph problem (DSP), Goldberg [31] devised a max-flow-based algorithm to obtain exact solutions in unweighted and weighted graphs.
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