Jun 5, 2021 · We search for a set of (overlapping) common subgraphs, that are connected in the physical network and densest in the conceptual network.
This paper proposes a novel graph classification method based on the subgraph-level feature the high-difference-frequency subgraph.
May 3, 2022 · The subgraph-based approach provides a systematic scenario for analyzing, compare and classifying molecular networks with diverse ...
Jul 30, 2024 · A third place (public social space) has been proven to be a gathering place for communities of friends on social networks (social media).
Graph neural network-based subgraph analysis for predicting ...
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This paper presents a state-of-the-art network-based approach that models patients as subgraphs composed of nodes of International Classification of Diseases ( ...
Jun 19, 2020 · Deep learning methods for graphs achieve remarkable performance on many node- level and graph-level prediction tasks.
A novel graph kernel based link prediction method is proposed by Yuan et al. to predict links by comparing user similarity via signed social network's.
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In this article, we focus on proposing a method for detecting communities of signed social networks and mining γ -Quasi-Cliques for closely related users ...
This work proposes a framework that accelerates community detection by applying an expensive algorithm (modularity optimization, the Louvain method, ...
Mar 1, 2020 · Different graph similarity/distance metrics are defined, such as Graph Edit Distance (GED) [4], Max- imum Common Subgraph (MCS) [6], etc.