Approximate Summaries for Why and Why-not Provenance
Summary: Proposes approximate summarization of why/why-not provenance via pattern encodings to compress provenance. Adds sampling for scalable capture and concise, informative summaries on large datasets, balancing informativeness, conciseness, and completeness. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Seokki Lee (Illinois Institute of Technology)
- 2. Bertram Ludäscher (University of Illinois Urbana-Champaign)
- 3. Boris Glavic (Illinois Institute of Technology)
BibTeX Citation
@article{lee_vldb20,
title = {{Approximate Summaries for Why and Why-not Provenance}},
author = {Lee, Seokki and Ludäscher, Bertram and Glavic, Boris},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {6},
pages = {912--924},
doi = {10.14778/3380750.3380760},
url = {https://doi.org/10.14778/3380750.3380760},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,396 | Putting Things into Context: Rich Explanations for Query Answers using Join Graphs | 2021 | SIGMOD | 6.2329373e-05 |
| 5,660 | Banzhaf Values for Facts in Query Answering | 2024 | SIGMOD | 6.1305635e-05 |
| 8,388 | Why Not Match: On Explanations of Event Pattern Queries | 2021 | SIGMOD | 5.4364073e-05 |
| 8,889 | Provenance-based Data Skipping | 2022 | VLDB | 5.3512428e-05 |
| 10,436 | Causal Explanations for Disparate Trends: Where and Why? | 2026 | SIGMOD | 5.093636e-05 |
| 10,557 | Database Views as Explanations for Relational Deep Learning | 2026 | VLDB | 5.093636e-05 |
| 10,701 | Unified Lineage System: Tracking Data Provenance at Scale | 2025 | SIGMOD | 5.093636e-05 |
| 11,170 | Counterfactual Explanation at Will, with Zero Privacy Leakage | 2024 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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