Multi-dimensional Selectivity Estimation Using Compressed Histogram Information
Summary: Multi-dimensional selectivity estimation for dependent attributes within a single relation, including multimedia feature vectors in multi-dimensional indexes. Compressed histogram information with a discrete cosine transform across many small buckets achieves low storage, low error, and update-friendly maintenance without full reconstructions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ju-Hong Lee (Korea Advanced Institute of Science and Technology)
- 2. Deok-Hwan Kim (Korea Advanced Institute of Science and Technology)
- 3. Chin-Wan Chung (Korea Advanced Institute of Science and Technology)
BibTeX Citation
@inproceedings{lee_sigmod99,
title = {{Multi-dimensional Selectivity Estimation Using Compressed Histogram Information}},
author = {Lee, Ju-Hong and Kim, Deok-Hwan and Chung, Chin-Wan},
series = {{SIGMOD} '99},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/304182.304200},
url = {https://dl.acm.org/doi/10.1145/304182.304200},
year = {1999}
}
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