The Descriptive Complexity of Subgraph Isomorphism Without Numerics
Sign Up to like & getrecommendations! Published in 2018 at "Theory of Computing Systems"
DOI: 10.1007/s00224-018-9864-3
Abstract: Let F be a connected graph with ℓ vertices. The existence of a subgraph isomorphic to F can be defined in first-order logic with quantifier depth no better than ℓ, simply because no first-order formula… read more here.
Keywords: descriptive complexity; connected graphs; quantifier depth; subgraph ... See more keywords
On solving the densest k-subgraph problem on large graphs
Sign Up to like & getrecommendations! Published in 2020 at "Optimization Methods and Software"
DOI: 10.1080/10556788.2019.1595620
Abstract: ABSTRACT The densest k-subgraph problem is the problem of finding a k-vertex subgraph of a graph with the maximum number of edges. In order to solve large instances of the densest k-subgraph problem, we introduce… read more here.
Keywords: densest subgraph; problem; subgraph problem; problem large ... See more keywords
Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs
Sign Up to like & getrecommendations! Published in 2023 at "PLOS Computational Biology"
DOI: 10.1101/2022.02.02.478784
Abstract: The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but… read more here.
Keywords: contact networks; structure; contact; subgraph ... See more keywords
Localization of nonbacktracking centrality on dense subgraphs of sparse networks.
Sign Up to like & getrecommendations! Published in 2022 at "Physical review. E"
DOI: 10.1103/physreve.107.014301
Abstract: The nonbacktracking matrix and the related nonbacktracking centrality (NBC) play a crucial role in models of percolation-type processes on networks, such as nonrecurrent epidemics. Here we study the localization of NBC in infinite sparse networks… read more here.
Keywords: network; localization; enclosing network; subgraph ... See more keywords
Top- $k$ Subgraph Query Based on Frequent Structure in Large-Scale Dynamic Graphs
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2885038
Abstract: Frequent structures have emerged as resolving the structural pattern mining issues, such as chemistry, Web applications, and other related problems. Top- ${k}$ subgraph query as an important technology of graph search is widely used in… read more here.
Keywords: tex math; query; subgraph; inline formula ... See more keywords
Optimizing the Coherence of a Network of Networks
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Control of Network Systems"
DOI: 10.1109/tcns.2020.2979884
Abstract: We study the problem of optimal network design in a network of networks, a graph composed of a set of disjoint subgraphs, and a set of designed edges between them. Nodes obey noisy consensus dynamics,… read more here.
Keywords: network networks; problem; subgraph; network ... See more keywords
Incremental Frequent Subgraph Mining on Large Evolving Graphs
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2017.2743075
Abstract: Frequent subgraph mining is a core graph operation used in many domains, such as graph data management and knowledge exploration, bioinformatics, and security. Most existing techniques target static graphs. However, modern applications, such as social… read more here.
Keywords: frequent subgraph; evolving graphs; large evolving; subgraph mining ... See more keywords
Subgraph Networks With Application to Structural Feature Space Expansion
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2019.2957755
Abstract: Real-world networks exhibit prominent hierarchical and modular structures, with various subgraphs as building blocks. Most existing studies simply consider distinct subgraphs as motifs and use only their numbers to characterize the underlying network. Although such… read more here.
Keywords: feature space; order; subgraph; structural feature ... See more keywords
Elementary Subgraph Features for Link Prediction With Neural Networks
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3132352
Abstract: The enclosing subgraph of a target link has been proved to be effective for prediction of potential links. However, it is still unclear what topological features of the subgraph play the key role in determining… read more here.
Keywords: subgraph features; elementary subgraph; subgraph; prediction ... See more keywords
Reinforced Causal Explainer for Graph Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3170302
Abstract: Explainability is crucial for probing graph neural networks (GNNs), answering questions like “Why the GNN model makes a certain prediction?”. Feature attribution is a prevalent technique of highlighting the explanatory subgraph in the input graph,… read more here.
Keywords: neural networks; reinforced causal; causal explainer; subgraph ... See more keywords
Adaptive Subgraph Neural Network with Reinforced Critical Structure Mining.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3235931
Abstract: While graph representation learning methods have shown success in various graph mining tasks, what knowledge is exploited for predictions is less discussed. This paper proposes a novel Adaptive Subgraph Neural Network named AdaSNN to find… read more here.
Keywords: neural network; adaptive subgraph; subgraph; graph ... See more keywords