Largest Triangle Sampling for Visualizing Time Series in Database
Summary: Proposes Iterative Largest Triangle Sampling (ILTS) with convex-hull acceleration for time-series visualization. It iteratively refines samples; uses precomputed hulls to guarantee largest triangle, yielding higher fidelity and speedups over brute force. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Lei Rui
- 2. Xiangdong Huang
- 3. Shaoxu Song
- 4. Chen Wang
- 5. Jianmin Wang
- 6. Zhao Cao
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,804 | M4: A Visualization-Oriented Time Series Data Aggregation | 2014 | VLDB | 0.00010481427 |
| 3,971 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD | 6.5733348e-05 |
| 4,628 | Sim-Piece: Highly Accurate Piecewise Linear Approximation through Similar Segment Merging | 2023 | VLDB | 6.0321252e-05 |
| 6,072 | OM3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series | 2023 | SIGMOD | 5.2230588e-05 |
| 6,296 | Visualization-aware Time Series Min-Max Caching with Error Bound Guarantees | 2024 | VLDB | 5.1199987e-05 |
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