Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes
Summary: Proposes a variable-size, overlapping-bucket histogram that adapts to local density to approximate multi-dimensional real-valued data distributions more compactly and accurately. Generalizes kernel density estimation for efficient approximation of aggregate range queries and compares favorably with existing methods on real and synthetic datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dimitrios Gunopulos (University of California Riverside)
- 2. George Kollios (Polytechnic University)
- 3. Carlotta Domeniconi (University of California Riverside)
- 4. Vassilis J. Tsotras (University of California Riverside)
BibTeX Citation
@inproceedings{gunopulos_sigmod00,
title = {{Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes}},
author = {Gunopulos, Dimitrios and Kollios, George and Domeniconi, Carlotta and Tsotras, Vassilis J.},
series = {{SIGMOD} '00},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/342009.335448},
url = {https://dl.acm.org/doi/10.1145/342009.335448},
year = {2000}
}Incoming Citations (Sorted by Pagerank)
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Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 136 | Join Synopses for Approximate Query Answering | 1999 | SIGMOD | 0.00030123303 |
| 448 | Self-tuning Histograms: Building Histograms Without Looking at Data | 1999 | SIGMOD | 0.00018292618 |
| 2,127 | Selectivity Estimation in Spatial Databases | 1999 | SIGMOD | 9.127762e-05 |
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