| 1,681 |
The iBench Integration Metadata Generator |
2016 |
VLDB |
9.8851118e-05 |
| 1,941 |
Interpretable Data-Based Explanations for Fairness Debugging |
2022 |
SIGMOD |
9.3297671e-05 |
| 2,051 |
Messing Up with BART: Error Generation for Evaluating Data-Cleaning Algorithms |
2016 |
VLDB |
9.1199511e-05 |
| 4,449 |
Data Debugging and Exploration with Vizier |
2019 |
SIGMOD |
6.5953404e-05 |
| 4,739 |
Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances |
2019 |
SIGMOD |
6.4441962e-05 |
| 4,868 |
Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers |
2019 |
SIGMOD |
6.3748367e-05 |
| 4,882 |
Value Invention in Data Exchange |
2013 |
SIGMOD |
6.3711076e-05 |
| 4,919 |
Efficient Answering of Historical What-if Queries |
2022 |
SIGMOD |
6.3544814e-05 |
| 5,151 |
CAPE: Explaining Outliers by Counterbalancing |
2019 |
VLDB |
6.2528145e-05 |
| 5,272 |
InferDB: In-Database Machine Learning Inference Using Indexes |
2024 |
VLDB |
6.2010954e-05 |
| 5,529 |
Putting Things into Context: Rich Explanations for Query Answers using Join Graphs |
2021 |
SIGMOD |
6.0935553e-05 |
| 6,046 |
Your notebook is not crumby enough, REPLace it |
2020 |
CIDR |
5.9052121e-05 |
| 6,486 |
Approximate Summaries for Why and Why-not Provenance |
2020 |
VLDB |
5.7686627e-05 |
| 6,714 |
TRAMP: Understanding the Behavior of Schema Mappings through Provenance |
2010 |
VLDB |
5.7000511e-05 |
| 6,794 |
Snapshot Semantics for Temporal Multiset Relations |
2019 |
VLDB |
5.6806763e-05 |
| 7,313 |
Debugging Transactions and Tracking their Provenance with Reenactment |
2017 |
VLDB |
5.5551018e-05 |
| 7,334 |
Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher |
2022 |
SIGMOD |
5.5498988e-05 |
| 7,773 |
The Perm Provenance Management System in Action |
2009 |
SIGMOD |
5.455099e-05 |
| 7,879 |
To Not Miss the Forest for the Trees - A Holistic Approach for Explaining Missing Answers over Nested Data |
2021 |
SIGMOD |
5.4341576e-05 |
| 8,426 |
Efficient Uncertainty Tracking for Complex Queries with Attribute-level Bounds |
2021 |
SIGMOD |
5.3350162e-05 |
| 8,495 |
Provenance-based Data Skipping |
2022 |
VLDB |
5.3304338e-05 |
| 8,886 |
FastPDB: Towards Bag-Probabilistic Queries at Interactive Speeds |
2025 |
SIGMOD |
5.2559789e-05 |
| 9,374 |
Efficient Approximation of Certain and Possible Answers for Ranking and Window Queries over Uncertain Data |
2023 |
VLDB |
5.1868213e-05 |
| 9,630 |
Debugging Data Exchange with Vagabond |
2011 |
VLDB |
5.1475628e-05 |
| 10,023 |
CaJaDE: Explaining Query Results by Augmenting Provenance with Context |
2022 |
VLDB |
5.0934925e-05 |
| 10,024 |
Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb |
2021 |
VLDB |
5.0934925e-05 |
| 10,179 |
Adaptive Schema Databases |
2017 |
CIDR |
5.0659942e-05 |
| 10,803 |
Efficient Query Repair for Aggregate Constraints |
2026 |
VLDB |
4.9793485e-05 |
| 10,988 |
Exploring the Benefits of Just-in-time Model Replacement |
2026 |
VLDB |
4.9793485e-05 |
| 11,013 |
Q-ACER: Query Aggregate Constraint Efficient Repair System |
2026 |
VLDB |
4.9793485e-05 |
| 11,095 |
Smallest Synthetic Witnesses for Conjunctive Queries |
2025 |
PODS |
4.9793485e-05 |
| 11,172 |
Zorro: Quantifying Uncertainty in Models & Predictions Arising from Dirty Data |
2025 |
SIGMOD |
4.9793485e-05 |
| 11,176 |
Alsatian: Optimizing Model Search for Deep Transfer Learning |
2025 |
SIGMOD |
4.9793485e-05 |
| 11,368 |
Stress-Testing ML Pipelines with Adversarial Data Corruption |
2025 |
VLDB |
4.9793485e-05 |
| 11,466 |
Towards an Objective Metric for Data Value Through Relevance |
2024 |
CIDR |
4.9793485e-05 |
| 12,237 |
Provenance Summaries for Answers and Non-Answers |
2018 |
VLDB |
4.9793485e-05 |
| 12,337 |
BART in Action: Error Generation and Empirical Evaluations of Data-Cleaning Systems |
2016 |
SIGMOD |
4.9793485e-05 |
| 12,432 |
Gain Control over your Integration Evaluations |
2015 |
VLDB |
4.9793485e-05 |
| 13,750 |
DataSense: Display Agnostic Data Documentation |
2021 |
CIDR |
- |
| 13,903 |
Sharing and Reproducing Database Applications |
2015 |
VLDB |
- |