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Akane: Perplexity-Guided Time Series Data Cleaning

Summary: Akane reframes time-series cleaning as perplexity minimization: exploit recurrent patterns like token n-grams, then pick edits under a cleaning budget to lower sequence perplexity. Key novelty is perplexity-guided dirty-point detection/repair with a 4-phase framework plus budget selection and pattern-aggregation heuristics. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
6953
Venue
SIGMOD
Year
2024
Pagerank
4.7965857e-05
Overall Rank
7,223 | 49.76%
DOI
10.1145/3654993

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