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Subgraph Matching Using Graph Neural Network 被引量:2

Subgraph Matching Using Graph Neural Network
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摘要 Subgraph matching problem is identifying a target subgraph in a graph. Graph neural network (GNN) is an artificial neural network model which is capable of processing general types of graph structured data. A graph may contain many subgraphs isomorphic to a given target graph. In this paper GNN is modeled to identify a subgraph that matches the target graph along with its characteristics. The simulation results show that GNN is capable of identifying a target sub-graph in a graph. Subgraph matching problem is identifying a target subgraph in a graph. Graph neural network (GNN) is an artificial neural network model which is capable of processing general types of graph structured data. A graph may contain many subgraphs isomorphic to a given target graph. In this paper GNN is modeled to identify a subgraph that matches the target graph along with its characteristics. The simulation results show that GNN is capable of identifying a target sub-graph in a graph.
出处 《Journal of Intelligent Learning Systems and Applications》 2012年第4期274-278,共5页 智能学习系统与应用(英文)
关键词 SUBGRAPH Matching GRAPH NEURAL NETWORK Backpropagation RECURRENT NEURAL NETWORK FEEDFORWARD NEURAL NETWORK Subgraph Matching Graph Neural Network Backpropagation Recurrent Neural Network Feedforward Neural Network
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