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    » Sampling time-based sliding windows in bounded space
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    JCST
    2008
    175views more  JCST 2008»
    Improved Approximate Detection of Duplicates for Data Streams Over Sliding Windows
    13 years 5 months ago
    Improved Approximate Detection of Duplicates for Data Streams Over Sliding Windows
    Download  www.ccf.org.cn
    Detecting duplicates in data streams is an important problem that has a wide range of applications. In general, precisely detecting duplicates in an unbounded data stream is not fe...
    Hong Shen, Yu Zhang
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    JACM
    2012
    199views Distributed and Parallel Com...» more  JACM 2012»
    Continuous sampling from distributed streams
    11 years 7 months ago
    Continuous sampling from distributed streams
    Download  www.cs.ust.hk
    A fundamental problem in data management is to draw and maintain a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With la...
    Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang
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    PODS
    2003
    ACM
    143views Database» more  PODS 2003»
    Maintaining variance and k-medians over data stream windows
    14 years 5 months ago
    Maintaining variance and k-medians over data stream windows
    Download  ilpubs.stanford.edu
    The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
    Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
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    ICCAD
    2006
    IEEE
    130views Hardware» more  ICCAD 2006»
    On bounding the delay of a critical path
    14 years 2 months ago
    On bounding the delay of a critical path
    Download  www.cecs.uci.edu
    Process variations cause different behavior of timingdependent effects across different chips. In this work, we analyze one example of timing-dependent effects, crosscoupling ...
    Leonard Lee, Li-C. Wang
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    DATAMINE
    2006
    230views more  DATAMINE 2006»
    Mining top-K frequent itemsets from data streams
    13 years 5 months ago
    Mining top-K frequent itemsets from data streams
    Download  www.cs.ust.hk
    Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
    Raymond Chi-Wing Wong, Ada Wai-Chee Fu
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