A Probabilistic Substructure-Based Approach for Graph Classification

@article{Moonesinghe2007APS,
  title={A Probabilistic Substructure-Based Approach for Graph Classification},
  author={H. D. K. Moonesinghe and Hamed Valizadegan and Samah Jamal Fodeh and Pang-Ning Tan},
  journal={19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)},
  year={2007},
  volume={1},
  pages={346-349}
}
Graph classification is an important data mining task that has attracted considerable attention recently. This paper presents a probabilistic substructure-based approach for classifying graph-based data. More specifically, we use a frequent subgraph mining algorithm to extract substructure based descriptors and apply the maximum entropy principle to build a classification model from the frequent subgraphs. We perform extensive experiments to compare the performance of the proposed approach… CONTINUE READING

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