 Introduction  Mathematical Framework  Graphical Representation  Empirical Evidence  Criticisms  References

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• Introduction & Motivation – Stream computation model, Applications • Basic stream synopses computation – Samples, Equi-depth histograms, Wavelets • Mining data streams – Decision trees, clustering, association rules • Sketch-based computation techniques – Self-joins, Joins, Wavelets, V-optimal histograms • Advanced techniques – Sliding windows, Distinct values, Hot lists • Future directions & Conclusions

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