Incremental, online, and merge mining of partial periodic patterns in time-series databases

@article{Aref2004IncrementalOA,
  title={Incremental, online, and merge mining of partial periodic patterns in time-series databases},
  author={Walid G. Aref and Mohamed G. Elfeky and Ahmed K. Elmagarmid},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2004},
  volume={16},
  pages={332-342}
}
  • Walid G. Aref, Mohamed G. Elfeky, Ahmed K. Elmagarmid
  • Published in
    IEEE Transactions on…
    2004
  • Computer Science
  • Mining of periodic patterns in time-series databases is an interesting data mining problem. It can be envisioned as a tool for forecasting and prediction of the future behavior of time-series data. Incremental mining refers to the issue of maintaining the discovered patterns over time in the presence of more items being added into the database. Because of the mostly append only nature of updating time-series data, incremental mining would be very effective and efficient. Several algorithms for… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 23 REFERENCES

    DEMON: mining and monitoring evolving data

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Efficient mining of partial periodic patterns in time series database

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Induction of Decision Trees

    VIEW 1 EXCERPT

    Efficient time series matching by wavelets

    VIEW 1 EXCERPT

    On similarity-based queries for time series data

    • Davood Rafiei
    • Computer Science
    • Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)
    • 1999
    VIEW 1 EXCERPT

    Online association rule mining

    VIEW 1 EXCERPT