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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
7068
Venue
SIGMOD
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,393 | 27.70%
DOI
10.1145/3709726

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Rank Citing Paper Year Venue Pagerank
10,449 PY-SHARQ: A Holistic Python Library for Explaining Association Rules on Relational Data 2025 SIGMOD 4.1945683e-05
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