A generative probabilistic approach to visualizing sets of symbolic sequences

@inproceedings{Tio2004AGP,
  title={A generative probabilistic approach to visualizing sets of symbolic sequences},
  author={Peter Ti{\~n}o and Ata Kab{\'a}n and Yi Sun},
  booktitle={KDD},
  year={2004}
}
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative probabilistic model for visualizing sets of discrete symbolic sequences. The model, a constrained mixture of discrete hidden Markov models, is a generalization of density-based visualization methods previously developed for static data sets. We illustrate our approach on sequences representing web-log data and chorals… CONTINUE READING

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HIGHLY INFLUENTIAL