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Outlier Summarization via Human Interpretable Rules

Summary: STAIR learns concise, human‑interpretable rules (attribute+value predicates) to summarize and explain outlier detection results with finer granularity via an interpretation‑aware objective and iterative rule‑splitting. L‑STAIR localizes learning per partition for high‑dimensional data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13400
Venue
VLDB
Year
2024
Pagerank
4.299267e-05
Overall Rank
9,709 | 32.46%
DOI
10.14778/3654621.3654627

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,475 OIE: An Interpretable System for Outlier Explanation and Summarization 2025 SIGMOD 4.3341665e-05
10,029 Outliers: The Good, the Bad and the Ugly 2026 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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