Article ID Journal Published Year Pages File Type
529994 Pattern Recognition 2015 14 Pages PDF
Abstract

•We present four novel n-neighbourhood topological node features.•We present three strengthening indices, used to enhance topological node features.•A new subgraph isomorphism algorithm is introduced, enhancing existing pruning techniques.

This paper presents techniques designed to minimise the number of states which are explored during subgraph isomorphism detection. A set of advanced topological node features, calculated from n-neighbourhood graphs, is presented and shown to outperform existing features. Further, the pruning effectiveness of both the new and existing topological node features is significantly improved through the introduction of strengthening techniques. In addition to topological node features, these strengthening techniques can also be used to enhance application-specific node labels using a proposed novel extension to existing pruning algorithms. Through the combination of these techniques, the number of explored search states can be reduced to near-optimal levels.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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