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Summarized Causal Explanations For Aggregate Views

Summary: CauSumX generates summarized causal explanations for entire aggregate views (group-by averages) via a causal DAG. It uses an optimization with Apriori+LP rounding to select group-specific causal treatments; scalable to high-dimensional data and outperforms prior work in usefulness and realism. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6942
Venue
SIGMOD
Year
2024
Pagerank
5.7362362e-05
Overall Rank
6,932 | 52.45%
DOI
10.1145/3639328

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{youngmann_sigmod24,
        title = {{Summarized Causal Explanations For Aggregate Views}},
        author = {Youngmann, Brit and Cafarella, Michael and Gilad, Amir and Roy, Sudeepa},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639328},
        url = {https://dl.acm.org/doi/10.1145/3639328},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 27 of 27 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
27 Fast Algorithms for Mining Association Rules 1994 VLDB 0.00052255472
191 Scorpion: Explaining Away Outliers in Aggregate Queries 2013 VLDB 0.00026096009
385 Why Not? 2009 SIGMOD 0.00019455743
605 The Complexity of Causality and Responsibility for Query Answers and non-Answers 2011 VLDB 0.00015839628
663 A Formal Approach to Finding Explanations for Database Queries 2014 SIGMOD 0.00015174751
806 Provenance for Aggregate Queries 2011 PODS 0.00013890398
858 Interpretable and Informative Explanations of Outcomes 2015 VLDB 0.0001356511
915 Intelligent Rollups in Multidimensional OLAP Data 2001 VLDB 0.00013243386
2,195 Explaining Query Answers with Explanation-Ready Databases 2016 VLDB 8.9713779e-05
2,374 Causal Relational Learning 2020 SIGMOD 8.6755064e-05
2,382 The Generalized MDL Approach for Summarization 2002 VLDB 8.6603462e-05
2,546 Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query) 2018 SIGMOD 8.4340413e-05
2,670 The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries 2020 PODS 8.2737143e-05
3,407 Quotient Cube: How to Summarize the Semantics of a Data Cube 2002 VLDB 7.4391131e-05
4,204 MDL Summarization with Holes 2005 VLDB 6.834169e-05
4,631 Interactive Summarization and Exploration of Top Aggregate Query Answers 2018 VLDB 6.595034e-05
4,638 Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances 2019 SIGMOD 6.5919801e-05
4,747 High-Level Why-Not Explanations using Ontologies 2015 PODS 6.5252099e-05
4,758 Constructing and Exploring Composite Items 2010 SIGMOD 6.521122e-05
4,876 XInsight: eXplainable Data Analysis Through The Lens of Causality 2023 SIGMOD 6.4687705e-05
5,025 HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach 2022 SIGMOD 6.3974766e-05
5,396 Putting Things into Context: Rich Explanations for Query Answers using Join Graphs 2021 SIGMOD 6.2329373e-05
6,054 Causal Data Integration 2023 VLDB 5.9932261e-05
7,003 Guided Exploration of Data Summaries 2022 VLDB 5.7278883e-05
8,184 FEDEX: An Explainability Framework for Data Exploration Steps 2022 VLDB 5.4709725e-05
8,719 DPXPlain: Privately Explaining Aggregate Query Answers 2023 VLDB 5.3774243e-05
11,617 On Detecting Cherry-picked Generalizations 2022 VLDB 5.093636e-05
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