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CAPE: Explaining Outliers by Counterbalancing

Summary: Explains surprising aggregation outcomes by counterbalancing with opposite-direction outliers. Defines coarse aggregate regression patterns (ARPs) and presents an efficient algorithm to surface counterbalances as explanations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11871
Venue
VLDB
Year
2019
Pagerank
5.6758584e-05
Overall Rank
5,128 | 64.33%
DOI
10.14778/3352063.3352071

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
5,916 Banzhaf Values for Facts in Query Answering 2024 SIGMOD 5.273953e-05
6,565 Toward Interpretable and Actionable Data Analysis with Explanations and Causality 2022 VLDB 5.0081626e-05
9,698 ExTuNe: Explaining Tuple Non-conformance 2020 SIGMOD 4.3022295e-05
9,709 Outlier Summarization via Human Interpretable Rules 2024 VLDB 4.299267e-05
10,029 Outliers: The Good, the Bad and the Ugly 2026 SIGMOD 4.1945683e-05
10,269 Database Views as Explanations for Relational Deep Learning 2026 VLDB 4.1945683e-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
31 Provenance Semirings 2007 PODS 0.0007857786
214 Scorpion: Explaining Away Outliers in Aggregate Queries 2013 VLDB 0.0003363692
942 A Formal Approach to Finding Explanations for Database Queries 2014 SIGMOD 0.00015155714
5,191 Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances 2019 SIGMOD 5.6378768e-05
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