ISSD: Indicator Selection for Time Series State Detection
Summary: ISSD frames indicator selection as upstream optimization for time-series state detection. Channel set completeness/quality from segment-level sampling drives a Pareto-front NP-hard approximation to a compact indicator subset; validated on multiple datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chengyu Wang
- 2. Tongqing Zhou
- 3. Lin Chen
- 4. Shan Zhao
- 5. Zhiping Cai
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,321 | CLaP - State Detection from Time Series | 2026 | VLDB | 5.1725247e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,344 | Finding Semantics in Time Series | 2011 | SIGMOD | 7.5619842e-05 |
| 4,309 | AutoPlait: Automatic Mining of Co-evolving Time Sequences | 2014 | SIGMOD | 6.8395788e-05 |
| 7,289 | Raising the ClaSS of Streaming Time Series Segmentation | 2024 | VLDB | 5.7096715e-05 |
| 9,170 | Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data | 2023 | SIGMOD | 5.371468e-05 |
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| 10,451 | KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection | 2025 | SIGMOD | 5.1725247e-05 |
| 10,321 | CLaP - State Detection from Time Series | 2026 | VLDB | 5.1725247e-05 |
| 9,170 | Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data | 2023 | SIGMOD | 5.371468e-05 |