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Automatic Segmentation of Data Sequences
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use average longest path instead of longest path (sum of weights) (ablation) | DASSA · ChickenDance 1 | F1: 0.63 -> 1 | Helped |
| use average longest path instead of longest path (sum of weights) (ablation) | DASSA · ChickenDance 2 | F1: 0.54 -> 1 | Helped |
| use average longest path instead of longest path (sum of weights) (ablation) | DASSA · Portland | F1: 0 -> 1 | Helped |
| use average longest path instead of longest path (sum of weights) (ablation) | DASSA · PUC-Rio | F1: 0.44 -> 0.66 | Helped |
| cluster data values with IB+MDL instead of topic modeling (ablation) | DASSA · ChickenDance 2 | F1: 0.6 -> 1 | Helped |
| cluster data values with IB+MDL instead of topic modeling (ablation) | DASSA · Portland | F1: 1 -> 1 | No clear effect |
| use cluster distribution p(x~|y) instead of empirical data distribution for segment distance (ablation) | DASSA · ChickenDance 2 | F1: 1 -> 0.90 | Hurt |
| use cluster distribution p(x~|y) instead of empirical data distribution (ablation) | DASSA · Portland | F1: 0.66 -> 1 | Helped |
| DASSA versus Dynammo with ground-truth cut count | DASSA · PUC-Rio | F1: 0.25 -> 0.66 | Helped |
Closest papers by meaning
- SnapNETS: Automatic Segmentation of Network Sequences with Node Labels (AAAI 2017 · similarity 0.84)
- Toward Interpretable Evaluation Measures for Time Series Segmentation (NeurIPS 2025 · similarity 0.82)
- Discovering Sequential Patterns with Predictable Inter-event Delays (AAAI 2024 · similarity 0.80)
- RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything (ICLR 2025 · similarity 0.80)
- Scaling up Image Segmentation across Data and Tasks (CVPR 2025 · similarity 0.80)
- RankSEG-RMA: An Efficient Segmentation Algorithm via Reciprocal Moment Approximation (NeurIPS 2025 · similarity 0.79)
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