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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)

Paper ID
7044
Venue
SIGMOD
Year
2025
Pagerank
5.371468e-05
Overall Rank
9,161 | 36.34%
DOI
10.1145/3709698

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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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