Efficient Haar+ Synopsis Construction for the Maximum Absolute Error Measure
Summary: Proposes efficient Haar+ synopsis construction for maximum absolute error measure by keeping a minimal set of optimal synopses per node. Also introduces coefficient-value restrictions and grouping into compact representations to speed up computation. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jinhyun Kim (Seoul National University)
- 2. Jun-Ki Min (Korea University)
- 3. Kyuseok Shim (Seoul National University)
BibTeX Citation
@article{kim_vldb18,
title = {{Efficient Haar+ Synopsis Construction for the Maximum Absolute Error Measure}},
author = {Kim, Jinhyun and Min, Jun-Ki and Shim, Kyuseok},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {1},
pages = {40--52},
doi = {10.14778/3136610.3136614},
url = {https://doi.org/10.14778/3136610.3136614},
year = {2018}
}
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