| 672 |
A Formal Approach to Finding Explanations for Database Queries |
2014 |
SIGMOD |
67 |
0.00014903109 |
| 1,314 |
Computing Optimal Repairs for Functional Dependencies |
2018 |
PODS |
25 |
0.000110547 |
| 1,989 |
Causality and Explanations in Databases |
2014 |
VLDB |
28 |
9.2277193e-05 |
| 2,233 |
Explaining Query Answers with Explanation-Ready Databases |
2016 |
VLDB |
29 |
8.7844607e-05 |
| 2,328 |
Causal Relational Learning |
2020 |
SIGMOD |
21 |
8.6206869e-05 |
| 2,497 |
Computing Local Sensitivities of Counting Queries with Joins |
2020 |
SIGMOD |
24 |
8.365674e-05 |
| 4,577 |
HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach |
2022 |
SIGMOD |
16 |
6.5111757e-05 |
| 4,742 |
Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances |
2019 |
SIGMOD |
17 |
6.4285195e-05 |
| 4,752 |
Interactive Summarization and Exploration of Top Aggregate Query Answers |
2018 |
VLDB |
11 |
6.4226993e-05 |
| 4,871 |
Explaining Wrong Queries Using Small Examples |
2019 |
SIGMOD |
16 |
6.3583165e-05 |
| 5,174 |
CAPE: Explaining Outliers by Counterbalancing |
2019 |
VLDB |
6 |
6.2291886e-05 |
| 5,556 |
Putting Things into Context: Rich Explanations for Query Answers using Join Graphs |
2021 |
SIGMOD |
14 |
6.0705311e-05 |
| 5,748 |
An Optimal Labeling Scheme for Workflow Provenance Using Skeleton Labels |
2010 |
SIGMOD |
6 |
5.9914851e-05 |
| 5,879 |
Properties of Inconsistency Measures for Databases |
2021 |
SIGMOD |
9 |
5.9438507e-05 |
| 6,126 |
iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks |
2019 |
SIGMOD |
5 |
5.8614712e-05 |
| 6,443 |
Evaluating Datalog over Semirings: A Grounding-based Approach |
2024 |
PODS |
5 |
5.7666211e-05 |
| 6,450 |
Summarized Causal Explanations For Aggregate Views |
2024 |
SIGMOD |
12 |
5.7635046e-05 |
| 6,550 |
Provenance Views for Module Privacy |
2011 |
PODS |
4 |
5.7316808e-05 |
| 6,668 |
Queries with Difference on Probabilistic Databases |
2011 |
VLDB |
2 |
5.6980608e-05 |
| 6,718 |
Toward Interpretable and Actionable Data Analysis with Explanations and Causality |
2022 |
VLDB |
4 |
5.6843134e-05 |
| 6,753 |
On Multiple Semantics for Declarative Database Repairs |
2020 |
SIGMOD |
14 |
5.673161e-05 |
| 7,175 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
6 |
5.5779755e-05 |
| 7,225 |
QAGView: Interactively Summarizing High-Valued Aggregate Query Answers |
2018 |
SIGMOD |
5 |
5.5652224e-05 |
| 7,355 |
Selectivity Functions of Range Queries are Learnable* |
2022 |
SIGMOD |
8 |
5.529034e-05 |
| 7,385 |
Enabling Privacy in Provenance-Aware Workflow Systems |
2011 |
CIDR |
4 |
5.5215471e-05 |
| 7,404 |
Aggregated Deletion Propagation for Counting Conjunctive Query Answers |
2021 |
VLDB |
5 |
5.5178575e-05 |
| 7,766 |
I-Rex: An Interactive Relational Query Explainer for SQL |
2020 |
VLDB |
5 |
5.4399564e-05 |
| 8,042 |
Optimizing Iceberg Queries with Complex Joins |
2017 |
SIGMOD |
4 |
5.3852464e-05 |
| 8,910 |
DPXPlain: Privately Explaining Aggregate Query Answers |
2023 |
VLDB |
9 |
5.2369069e-05 |
| 9,001 |
Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries |
2024 |
SIGMOD |
4 |
5.2260584e-05 |
| 9,035 |
The Cost of Representation by Subset Repairs |
2025 |
VLDB |
2 |
5.2191717e-05 |
| 9,044 |
LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers |
2019 |
VLDB |
3 |
5.2176863e-05 |
| 9,090 |
Understanding Queries by Conditional Instances |
2022 |
SIGMOD |
6 |
5.2092307e-05 |
| 9,990 |
Fair and Actionable Causal Prescription Ruleset |
2025 |
SIGMOD |
2 |
5.0845476e-05 |
| 10,027 |
Opportunities for Data Management Research in the Era of Horizontal AI/ML |
2019 |
VLDB |
1 |
5.0817642e-05 |
| 10,066 |
CaJaDE: Explaining Query Results by Augmenting Provenance with Context |
2022 |
VLDB |
2 |
5.074247e-05 |
| 10,155 |
iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks |
2018 |
SIGMOD |
3 |
5.0597449e-05 |
| 10,469 |
A Unifying Algorithm for Hierarchical Queries |
2026 |
PODS |
0 |
4.9605343e-05 |
| 10,914 |
I-Rex: An Interactive Debugger for SQL |
2026 |
VLDB |
0 |
4.9605343e-05 |
| 11,036 |
Qr-Hint: Formally Verified and AI-Explained SQL Tutoring |
2026 |
VLDB |
0 |
4.9605343e-05 |
| 11,153 |
Circuits and Formulas for Datalog over Semirings |
2025 |
PODS |
0 |
4.9605343e-05 |
| 11,211 |
CauSumX: Summarized Causal Explanations For Group-By-Average Queries |
2025 |
SIGMOD |
0 |
4.9605343e-05 |
| 11,458 |
Hint-QPT: Hints for Robust Query Performance Tuning |
2025 |
VLDB |
2 |
4.9605343e-05 |
| 11,719 |
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms |
2024 |
VLDB |
1 |
4.9605343e-05 |
| 11,840 |
Explaining Differentially Private Query Results With DPXPlain |
2023 |
VLDB |
0 |
4.9605343e-05 |
| 12,163 |
MuSe: Multiple Deletion Semantics for Data Repair |
2020 |
VLDB |
1 |
4.9605343e-05 |
| 12,210 |
RATest: Explaining Wrong Relational Queries Using Small Examples |
2019 |
SIGMOD |
3 |
4.9605343e-05 |
| 12,590 |
Provenance-based Dictionary Refinement in Information Extraction |
2013 |
SIGMOD |
0 |
4.9605343e-05 |
| 13,684 |
PACMMOD V3, N4 (SIGMOD), September 2025: Editorial |
2025 |
SIGMOD |
0 |
- |