ASAP: Prioritizing Attention via Time Series Smoothing
Summary: ASAP: smoothing time series to highlight long-term trends. Novel operator optimizes var–kurt with autocorrelation pruning and pixel-aware preaggregation; on-demand refresh yields 38.4% accuracy gains and 44.3% latency reductions, faster than work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kexin Rong (Stanford University)
- 2. Peter Bailis (Stanford University)
BibTeX Citation
@article{rong_vldb17,
title = {{ASAP: Prioritizing Attention via Time Series Smoothing}},
author = {Rong, Kexin and Bailis, Peter},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {11},
pages = {1358--1369},
doi = {10.14778/3137628.3137630},
url = {https://doi.org/10.14778/3137628.3137630},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,392 | Northstar: An Interactive Data Science System | 2018 | VLDB | 0.00010936065 |
| 6,073 | OnlineSTL: Scaling Time Series Decomposition by 100x | 2022 | VLDB | 5.9862575e-05 |
| 9,713 | TSExplain: Surfacing Evolving Explanations for Time Series | 2021 | SIGMOD | 5.2342614e-05 |
| 10,353 | Cleaning Time Series under Seasonal and Trend Constraints | 2026 | SIGMOD | 5.093636e-05 |
| 11,932 | Vocalizing Large Time Series Efficiently | 2018 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
| 371 | Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases | 1995 | VLDB | 0.00019869565 |
| 986 | Effortless Data Exploration with zenvisage: An Expressive and Interactive Visual Analytics System | 2017 | VLDB | 0.0001281777 |
| 1,263 | Resource Sharing in Continuous Sliding-Window Aggregates | 2004 | VLDB | 0.00011425419 |
| 1,472 | M4: A Visualization-Oriented Time Series Data Aggregation | 2014 | VLDB | 0.00010668946 |
| 1,792 | MacroBase: Prioritizing Attention in Fast Data | 2017 | SIGMOD | 9.7436856e-05 |
| 2,802 | General Incremental Sliding-Window Aggregation | 2015 | VLDB | 8.1093063e-05 |
| 3,359 | VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Databases | 2004 | VLDB | 7.4898575e-05 |
| 4,207 | Combining Databases and Signal Processing in Plato | 2015 | CIDR | 6.8325104e-05 |
| 5,329 | SeeDB: Visualizing Database Queries Efficiently | 2014 | VLDB | 6.2634965e-05 |
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|---|---|---|---|---|
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| 3 | 11,962 | Prioritizing Attention in Fast Data: Principles and Promise | 2017 | CIDR |
| 4 | 6,007 | OM3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series | 2023 | SIGMOD |
| 5 | 1,472 | M4: A Visualization-Oriented Time Series Data Aggregation | 2014 | VLDB |
| 6 | 1,634 | Rapid Sampling for Visualizations with Ordering Guarantees | 2015 | VLDB |
| 7 | 9,757 | Faster Visual Analytics through Pixel-Perfect Aggregation | 2014 | VLDB |
| 8 | 3,288 | I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making | 2017 | VLDB |
| 9 | 10,415 | Visualization-Oriented Progressive Time Series Transformation | 2026 | SIGMOD |
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