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Wavelet density estimators over data streams

Published: 13 March 2005 Publication History

Abstract

Density estimation is a building block of many data analysis techniques. A recently examined approach based on wavelets promises to be superior to traditional density estimation techniques. For possibly infinite data streams, however, this approach is not feasible due to the limited resources, e.g. memory. In this paper, we propose a new technique for computing wavelet density estimators over data streams that only requires a fixed amount of memory. Our estimators are updated in an online manner such that a continuous analysis of data streams is supported during runtime.

References

[1]
B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom. Models and Issues in Data Stream Systems. In Symp. on Principles of Database Systems, 2002.
[2]
B. Blohsfeld, C. Heinz, and B. Seeger. Maintaining Nonparametric Estimators over Data Streams. Technical Report No. 39, Philipps-University Marburg, 2004.
[3]
P. Domingos and G. Hulten. A general framework for mining massive data streams. Journal of Computational and Graphical Statistics, 2003.
[4]
D. W. Scott. Multivariate Density Estimation. Theory, Practice, and Visualization. John Wiley & Sons, New York, 1992.
[5]
B. Vidakovic. Statistical Modeling by Wavelets. John Wiley & Sons, New York, 1999.

Cited By

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  • (2008)Fast online estimation of the joint probability distributionProceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining10.5555/1786574.1786643(689-696)Online publication date: 20-May-2008
  • (2008)Fast Online Estimation of the Joint Probability DistributionAdvances in Knowledge Discovery and Data Mining10.1007/978-3-540-68125-0_65(689-696)Online publication date: 2008
  • (2006)Exploring Data Streams with Nonparametric EstimatorsProceedings of the 18th International Conference on Scientific and Statistical Database Management10.1109/SSDBM.2006.25(261-264)Online publication date: 3-Jul-2006
  • Show More Cited By

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  1. Wavelet density estimators over data streams

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    cover image ACM Conferences
    SAC '05: Proceedings of the 2005 ACM symposium on Applied computing
    March 2005
    1814 pages
    ISBN:1581139640
    DOI:10.1145/1066677
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 13 March 2005

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    Author Tags

    1. data streams
    2. density estimation
    3. wavelets

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    SAC05
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    SAC05: The 2005 ACM Symposium on Applied Computing
    March 13 - 17, 2005
    New Mexico, Santa Fe

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    Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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    Cited By

    View all
    • (2008)Fast online estimation of the joint probability distributionProceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining10.5555/1786574.1786643(689-696)Online publication date: 20-May-2008
    • (2008)Fast Online Estimation of the Joint Probability DistributionAdvances in Knowledge Discovery and Data Mining10.1007/978-3-540-68125-0_65(689-696)Online publication date: 2008
    • (2006)Exploring Data Streams with Nonparametric EstimatorsProceedings of the 18th International Conference on Scientific and Statistical Database Management10.1109/SSDBM.2006.25(261-264)Online publication date: 3-Jul-2006
    • (2006)Stream Processing in Production-to-Business SoftwareProceedings of the 22nd International Conference on Data Engineering10.1109/ICDE.2006.148Online publication date: 3-Apr-2006

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