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NETS: Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing

Summary: Set-based outlier detection on streams by grouping nearby points, enabling early identification and avoiding repetitive distance calculations across sliding windows. Two-level dimensional filtering scales to high dimensions, delivering 5–25x faster processing than state-of-the-art with comparable memory. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11826
Venue
VLDB
Year
2019
Pagerank
7.7153586e-05
Overall Rank
3,012 | 79.05%
DOI
10.14778/3342263.3342269

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