Scorpion: Explaining Away Outliers in Aggregate Queries
Summary: Scorpion takes user-specified outlier points from aggregate results and derives input predicates that remove those outliers. Defines predicate influence and uses efficient max-influence search to reveal explanations faster than naive search. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Eugene Wu (Massachusetts Institute of Technology)
- 2. Samuel Madden (Massachusetts Institute of Technology)
BibTeX Citation
@article{wu_vldb13,
title = {{Scorpion: Explaining Away Outliers in Aggregate Queries}},
author = {Wu, Eugene and Madden, Samuel},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {8},
pages = {553--564},
doi = {10.14778/2536206.2536209},
url = {https://doi.org/10.14778/2536206.2536209},
year = {2013}
}
Incoming Citations (Sorted by Pagerank)
Showing 50 of 83 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 308 | Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications | 1998 | SIGMOD | 0.00021473921 |
| 700 | Explaining differences in multidimensional aggregates | 1999 | VLDB | 0.00014681669 |
| 925 | Intelligent Rollups in Multidimensional OLAP Data | 2001 | VLDB | 0.00013051939 |
| 1,615 | Sensitivity Analysis and Explanations for Robust Query Evaluation in Probabilistic Databases | 2011 | SIGMOD | 0.00010067073 |
| 1,708 | PerfXplain: Debugging MapReduce Job Performance | 2012 | VLDB | 9.8224587e-05 |
| 1,785 | Approximate Lineage for Probabilistic Databases | 2008 | VLDB | 9.6482655e-05 |
| 2,458 | Tracing Data Errors with View-Conditioned Causality | 2011 | SIGMOD | 8.4371456e-05 |
| 3,035 | MRI: Meaningful Interpretations of Collaborative Ratings | 2011 | VLDB | 7.7329528e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,703 | Interactive Query Explanations Using Fine Grained Provenance | 2022 | SIGMOD |
| 2 | 583 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD |
| 3 | 7,421 | Efficient Evaluation of Object-Centric Exploration Queries for Visualization | 2015 | VLDB |
| 4 | 6,904 | Sharing-Aware Outlier Analytics over High-Volume Data Streams | 2016 | SIGMOD |
| 5 | 695 | Algorithms for Mining Distance-Based Outliers in Large Datasets | 1998 | VLDB |
| 6 | 5,151 | CAPE: Explaining Outliers by Counterbalancing | 2019 | VLDB |
| 7 | 10,393 | Clustering with Set Outliers and Applications in Relational Clustering | 2026 | PODS |
| 8 | 2,222 | Explaining Query Answers with Explanation-Ready Databases | 2016 | VLDB |
| 9 | 7,955 | Distributed Outlier Detection using Compressive Sensing | 2015 | SIGMOD |
| 10 | 4,739 | Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances | 2019 | SIGMOD |