| 648 |
A Formal Approach to Finding Explanations for Database Queries |
2014 |
SIGMOD |
0.00015479019 |
| 1,895 |
Causality and Explanations in Databases |
2014 |
VLDB |
9.6219591e-05 |
| 2,128 |
Explaining Query Answers with Explanation-Ready Databases |
2016 |
VLDB |
9.1839329e-05 |
| 2,378 |
Causal Relational Learning |
2020 |
SIGMOD |
8.7404828e-05 |
| 2,481 |
Computing Local Sensitivities of Counting Queries with Joins |
2020 |
SIGMOD |
8.6000811e-05 |
| 4,558 |
Interactive Summarization and Exploration of Top Aggregate Query Answers |
2018 |
VLDB |
6.697176e-05 |
| 4,562 |
Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances |
2019 |
SIGMOD |
6.6958473e-05 |
| 4,990 |
HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach |
2022 |
SIGMOD |
6.4792672e-05 |
| 5,008 |
CAPE: Explaining Outliers by Counterbalancing |
2019 |
VLDB |
6.4715689e-05 |
| 5,279 |
Explaining Wrong Queries Using Small Examples |
2019 |
SIGMOD |
6.35884e-05 |
| 5,329 |
Putting Things into Context: Rich Explanations for Query Answers using Join Graphs |
2021 |
SIGMOD |
6.3311372e-05 |
| 5,644 |
An Optimal Labeling Scheme for Workflow Provenance Using Skeleton Labels |
2010 |
SIGMOD |
6.2022353e-05 |
| 6,012 |
iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks |
2019 |
SIGMOD |
6.0702116e-05 |
| 6,215 |
Evaluating Datalog over Semirings: A Grounding-based Approach |
2024 |
PODS |
6.01306e-05 |
| 6,327 |
Provenance Views for Module Privacy |
2011 |
PODS |
5.9730345e-05 |
| 6,341 |
Properties of Inconsistency Measures for Databases |
2021 |
SIGMOD |
5.9698241e-05 |
| 6,436 |
Queries with Difference on Probabilistic Databases |
2011 |
VLDB |
5.9412426e-05 |
| 6,510 |
Toward Interpretable and Actionable Data Analysis with Explanations and Causality |
2022 |
VLDB |
5.9130342e-05 |
| 6,545 |
On Multiple Semantics for Declarative Database Repairs |
2020 |
SIGMOD |
5.9036536e-05 |
| 6,812 |
Summarized Causal Explanations For Aggregate Views |
2024 |
SIGMOD |
5.8250773e-05 |
| 6,937 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
5.804488e-05 |
| 6,946 |
QAGView: Interactively Summarizing High-Valued Aggregate Query Answers |
2018 |
SIGMOD |
5.8030544e-05 |
| 7,092 |
Selectivity Functions of Range Queries are Learnable* |
2022 |
SIGMOD |
5.7588694e-05 |
| 7,095 |
Enabling Privacy in Provenance-Aware Workflow Systems |
2011 |
CIDR |
5.7575126e-05 |
| 7,840 |
Optimizing Iceberg Queries with Complex Joins |
2017 |
SIGMOD |
5.6030414e-05 |
| 8,102 |
I-Rex: An Interactive Relational Query Explainer for SQL |
2020 |
VLDB |
5.5447897e-05 |
| 8,661 |
Aggregated Deletion Propagation for Counting Conjunctive Query Answers |
2021 |
VLDB |
5.4593674e-05 |
| 8,716 |
The Cost of Representation by Subset Repairs |
2025 |
VLDB |
5.4422152e-05 |
| 8,725 |
LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers |
2019 |
VLDB |
5.4406663e-05 |
| 8,864 |
Understanding Queries by Conditional Instances |
2022 |
SIGMOD |
5.4202259e-05 |
| 9,607 |
Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries |
2024 |
SIGMOD |
5.3068114e-05 |
| 9,629 |
Fair and Actionable Causal Prescription Ruleset |
2025 |
SIGMOD |
5.3018378e-05 |
| 9,654 |
Opportunities for Data Management Research in the Era of Horizontal AI/ML |
2019 |
VLDB |
5.2988078e-05 |
| 9,712 |
CaJaDE: Explaining Query Results by Augmenting Provenance with Context |
2022 |
VLDB |
5.2859392e-05 |
| 9,759 |
DPXPlain: Privately Explaining Aggregate Query Answers |
2023 |
VLDB |
5.2759752e-05 |
| 9,769 |
iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks |
2018 |
SIGMOD |
5.2759752e-05 |
| 10,000 |
A Unifying Algorithm for Hierarchical Queries |
2026 |
PODS |
5.1725247e-05 |
| 10,356 |
Circuits and Formulas for Datalog over Semirings |
2025 |
PODS |
5.1725247e-05 |
| 10,439 |
CauSumX: Summarized Causal Explanations For Group-By-Average Queries |
2025 |
SIGMOD |
5.1725247e-05 |
| 10,813 |
Hint-QPT: Hints for Robust Query Performance Tuning |
2025 |
VLDB |
5.1725247e-05 |
| 11,146 |
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms |
2024 |
VLDB |
5.1725247e-05 |
| 11,283 |
Explaining Differentially Private Query Results With DPXPlain |
2023 |
VLDB |
5.1725247e-05 |
| 11,620 |
MuSe: Multiple Deletion Semantics for Data Repair |
2020 |
VLDB |
5.1725247e-05 |
| 11,671 |
RATest: Explaining Wrong Relational Queries Using Small Examples |
2019 |
SIGMOD |
5.1725247e-05 |
| 12,060 |
Provenance-based Dictionary Refinement in Information Extraction |
2013 |
SIGMOD |
5.1725247e-05 |
| 13,125 |
PACMMOD V3, N4 (SIGMOD), September 2025: Editorial |
2025 |
SIGMOD |
- |