SHARQ: Explainability Framework for Association Rules on Relational Data

Summary: SHARQ quantifies an element’s contribution to relational association rules via Shapley values. Exact single-element SHARQ runs near-linear in rule count; a multi-element version amortizes cost, enabling rule- and attribute-importance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 7130
Venue: SIGMOD
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 10,679 | 26.74%
DOI: 10.1145/3709726

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Hadar Ben-Efraim (Bar-Ilan University)
2. Susan B. Davidson (University of Pennsylvania)
3. Amit Somech (Bar-Ilan University)

BibTeX Citation

@inproceedings{benefraim_sigmod25,
        title = {{SHARQ: Explainability Framework for Association Rules on Relational Data}},
        author = {Ben-Efraim, Hadar and Davidson, Susan B. and Somech, Amit},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709726},
        url = {https://dl.acm.org/doi/10.1145/3709726},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,730	PY-SHARQ: A Holistic Python Library for Explaining Association Rules on Relational Data	2025	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
13	Mining Association Rules between Sets of Items in Large Databases	1993	SIGMOD	0.0006567919
17	Provenance Semirings	2007	PODS	0.00059843817
27	Fast Algorithms for Mining Association Rules	1994	VLDB	0.00052255472
161	Mining Frequent Patterns without Candidate Generation	2000	SIGMOD	0.00027981772
191	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.00026096009
385	Why Not?	2009	SIGMOD	0.00019455743
460	Mining Generalized Association Rules	1995	VLDB	0.00018071773
704	Dynamic Itemset Counting and Implication Rules for Market Basket Data	1997	SIGMOD	0.00014837704
711	Beyond Market Baskets: Generalizing Association Rules to Correlations	1997	SIGMOD	0.00014713746
806	Provenance for Aggregate Queries	2011	PODS	0.00013890398
3,132	Extracting Top-K Insights from Multi-dimensional Data	2017	SIGMOD	7.7246394e-05
4,249	Exploratory Keyword Search with Interactive Input	2015	SIGMOD	6.8042877e-05
5,824	ShapGraph: An Holistic View of Explanations through Provenance Graphs and Shapley Values	2022	SIGMOD	6.0750989e-05
7,383	ExplainED: Explanations for EDA Notebooks	2020	VLDB	5.6284447e-05
7,399	ExRank: An Exploratory Ranking Interface	2016	VLDB	5.6255964e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	2,670	The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries	2020	PODS
2	4,154	A New SQL-like Operator for Mining Association Rules	1996	VLDB
3	10,214	CoShap: A Scalable Coalition Growth Approach to Shapley Value Approximation	2026	SIGMOD
4	9,809	Shapley Revisited: Tractable Responsibility Measures for Query Answers	2025	PODS
5	606	Mining Quantitative Association Rules in Large Relational Tables	1996	SIGMOD
6	5,382	Expected Shapley-Like Scores of Boolean Functions: Complexity and Applications to Probabilistic Databases	2024	PODS
7	2,424	Computing the Shapley Value of Facts in Query Answering	2022	SIGMOD
8	5,824	ShapGraph: An Holistic View of Explanations through Provenance Graphs and Shapley Values	2022	SIGMOD
9	13,324	ShaRP: Explaining Rankings and Preferences with Shapley Values	2025	VLDB
10	10,730	PY-SHARQ: A Holistic Python Library for Explaining Association Rules on Relational Data	2025	SIGMOD