| 671 |
A Formal Approach to Finding Explanations for Database Queries |
2014 |
SIGMOD |
67 |
0.00014948069 |
| 1,362 |
Computing Optimal Repairs for Functional Dependencies |
2018 |
PODS |
24 |
0.00010912749 |
| 1,983 |
Causality and Explanations in Databases |
2014 |
VLDB |
28 |
9.2548712e-05 |
| 2,222 |
Explaining Query Answers with Explanation-Ready Databases |
2016 |
VLDB |
29 |
8.8106741e-05 |
| 2,318 |
Causal Relational Learning |
2020 |
SIGMOD |
21 |
8.6491185e-05 |
| 2,488 |
Computing Local Sensitivities of Counting Queries with Joins |
2020 |
SIGMOD |
24 |
8.3933335e-05 |
| 4,568 |
HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach |
2022 |
SIGMOD |
16 |
6.5279657e-05 |
| 4,731 |
Interactive Summarization and Exploration of Top Aggregate Query Answers |
2018 |
VLDB |
11 |
6.4440072e-05 |
| 4,741 |
Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances |
2019 |
SIGMOD |
17 |
6.4411456e-05 |
| 4,849 |
Explaining Wrong Queries Using Small Examples |
2019 |
SIGMOD |
16 |
6.3794032e-05 |
| 5,152 |
CAPE: Explaining Outliers by Counterbalancing |
2019 |
VLDB |
6 |
6.2498545e-05 |
| 5,533 |
Putting Things into Context: Rich Explanations for Query Answers using Join Graphs |
2021 |
SIGMOD |
14 |
6.0906707e-05 |
| 5,749 |
An Optimal Labeling Scheme for Workflow Provenance Using Skeleton Labels |
2010 |
SIGMOD |
6 |
6.0051184e-05 |
| 5,866 |
Properties of Inconsistency Measures for Databases |
2021 |
SIGMOD |
9 |
5.96357e-05 |
| 6,113 |
iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks |
2019 |
SIGMOD |
5 |
5.880013e-05 |
| 6,432 |
Evaluating Datalog over Semirings: A Grounding-based Approach |
2024 |
PODS |
5 |
5.7857524e-05 |
| 6,438 |
Summarized Causal Explanations For Aggregate Views |
2024 |
SIGMOD |
12 |
5.7826256e-05 |
| 6,540 |
Provenance Views for Module Privacy |
2011 |
PODS |
4 |
5.7506962e-05 |
| 6,657 |
Queries with Difference on Probabilistic Databases |
2011 |
VLDB |
2 |
5.7169618e-05 |
| 6,703 |
Toward Interpretable and Actionable Data Analysis with Explanations and Causality |
2022 |
VLDB |
4 |
5.7031717e-05 |
| 6,734 |
On Multiple Semantics for Declarative Database Repairs |
2020 |
SIGMOD |
14 |
5.6919385e-05 |
| 7,152 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
6 |
5.5959861e-05 |
| 7,207 |
QAGView: Interactively Summarizing High-Valued Aggregate Query Answers |
2018 |
SIGMOD |
5 |
5.5836855e-05 |
| 7,334 |
Selectivity Functions of Range Queries are Learnable* |
2022 |
SIGMOD |
8 |
5.5473714e-05 |
| 7,366 |
Enabling Privacy in Provenance-Aware Workflow Systems |
2011 |
CIDR |
4 |
5.5398653e-05 |
| 7,385 |
Aggregated Deletion Propagation for Counting Conjunctive Query Answers |
2021 |
VLDB |
5 |
5.5361635e-05 |
| 7,752 |
I-Rex: An Interactive Relational Query Explainer for SQL |
2020 |
VLDB |
5 |
5.4580039e-05 |
| 8,028 |
Optimizing Iceberg Queries with Complex Joins |
2017 |
SIGMOD |
4 |
5.4028948e-05 |
| 8,890 |
DPXPlain: Privately Explaining Aggregate Query Answers |
2023 |
VLDB |
9 |
5.2542808e-05 |
| 8,981 |
Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries |
2024 |
SIGMOD |
4 |
5.2433963e-05 |
| 9,014 |
The Cost of Representation by Subset Repairs |
2025 |
VLDB |
2 |
5.2364868e-05 |
| 9,023 |
LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers |
2019 |
VLDB |
3 |
5.2349965e-05 |
| 9,069 |
Understanding Queries by Conditional Instances |
2022 |
SIGMOD |
6 |
5.2265129e-05 |
| 9,957 |
Fair and Actionable Causal Prescription Ruleset |
2025 |
SIGMOD |
2 |
5.1014161e-05 |
| 9,992 |
Opportunities for Data Management Research in the Era of Horizontal AI/ML |
2019 |
VLDB |
1 |
5.0986198e-05 |
| 10,028 |
CaJaDE: Explaining Query Results by Augmenting Provenance with Context |
2022 |
VLDB |
2 |
5.0910813e-05 |
| 10,118 |
iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks |
2018 |
SIGMOD |
3 |
5.0765311e-05 |
| 10,403 |
A Unifying Algorithm for Hierarchical Queries |
2026 |
PODS |
0 |
4.9769913e-05 |
| 10,853 |
I-Rex: An Interactive Debugger for SQL |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 10,975 |
Qr-Hint: Formally Verified and AI-Explained SQL Tutoring |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 11,092 |
Circuits and Formulas for Datalog over Semirings |
2025 |
PODS |
0 |
4.9769913e-05 |
| 11,152 |
CauSumX: Summarized Causal Explanations For Group-By-Average Queries |
2025 |
SIGMOD |
0 |
4.9769913e-05 |
| 11,405 |
Hint-QPT: Hints for Robust Query Performance Tuning |
2025 |
VLDB |
2 |
4.9769913e-05 |
| 11,673 |
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms |
2024 |
VLDB |
1 |
4.9769913e-05 |
| 11,796 |
Explaining Differentially Private Query Results With DPXPlain |
2023 |
VLDB |
0 |
4.9769913e-05 |
| 12,119 |
MuSe: Multiple Deletion Semantics for Data Repair |
2020 |
VLDB |
1 |
4.9769913e-05 |
| 12,167 |
RATest: Explaining Wrong Relational Queries Using Small Examples |
2019 |
SIGMOD |
3 |
4.9769913e-05 |
| 12,547 |
Provenance-based Dictionary Refinement in Information Extraction |
2013 |
SIGMOD |
0 |
4.9769913e-05 |
| 13,644 |
PACMMOD V3, N4 (SIGMOD), September 2025: Editorial |
2025 |
SIGMOD |
0 |
- |