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Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets

Summary: Wavelet-based compact data cube for sparse, high-dimensional data enables approximate OLAP aggregates. Two I/O-efficient construction algorithms; online queries require one to a few I/Os with tunable accuracy, outperforming histograms and random sampling. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3161
Venue
SIGMOD
Year
1999
Pagerank
0.00024723025
Overall Rank
213 | 98.55%
DOI
10.1145/304182.304199

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{vitter_sigmod99,
        title = {{Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets}},
        author = {Vitter, Jeffrey Scott and Wang, Min},
        series = {{SIGMOD} '99},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/304182.304199},
        url = {https://dl.acm.org/doi/10.1145/304182.304199},
        year = {1999}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 53 citing papers.

Rank Citing Paper Year Venue Pagerank
12,532 A Wavelet Transform for Efficient Consolidation of Sensor Relations with Quality Guarantees 2009 VLDB 5.093636e-05
12,803 AIMS: An Immersidata Management System 2003 CIDR 5.093636e-05
12,836 How to Evaluate Multiple Range-Sum Queries Progressively 2002 PODS 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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