Abstract
In this paper, a new method for graph and subgraph isomorphism detection based on a decision tree representation is proposed. The decision tree is generated off-line from a priori known model graphs. At run time the decision tree is used to detect all graph and subgraph isomorphisms from an input graph to any of the model graphs in time that is only polynomial in the size of the graphs and independent of the number of model graphs. However, the decision tree is of exponential size. In order to reduce the size of the decision tree, we propose two pruning techniques. Experimental results confirming the efficiency of the method will be given.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.