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One-pass wavelet decompositions of data streams

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4 Author(s)

We present techniques for computing small space representations of massive data streams. These are inspired by traditional wavelet-based approximations that consist of specific linear projections of the underlying data. We present general "sketch"-based methods for capturing various linear projections and use them to provide pointwise and rangesum estimation of data streams. These methods use small amounts of space and per-item time while streaming through the data and provide accurate representation as our experiments with real data streams show.

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Knowledge and Data Engineering, IEEE Transactions on  (Volume:15 ,  Issue: 3 )