Spatial pattern discovery by learning a probabilistic parametric model from multiple attributed relational graphs

@article{Hong2004SpatialPD,
  title={Spatial pattern discovery by learning a probabilistic parametric model from multiple attributed relational graphs},
  author={Pengyu Hong and Thomas S. Huang},
  journal={Discrete Applied Mathematics},
  year={2004},
  volume={139},
  pages={113-135}
}
This paper presents the methodology and theory for automatic spatial pattern discovery from multiple attributed relational graph samples. The spatial pattern is modelled as a mixture of probabilistic parametric attributed relational graphs. A statistic learning procedure is designed to learn the parameters of the spatial pattern model from the attributed relational graph samples. The learning procedure is formulated as a combinatorial non-deterministic process, which uses the Expectation… CONTINUE READING
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