PY-SHARQ: A Holistic Python Library for Explaining Association Rules on Relational Data
Summary: Demo of PY-SHARQ, a Python library for explaining association rules on relational data, using SHARQ (Shapley-based element contribution) to quantify influence in a rule set. Enables element-, rule-, and attribute-level importance analyses, addressing gaps beyond ITop/Infl. (summarized by gpt-5-nano on Feb 09 2026)
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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 = {{PY-SHARQ: A Holistic Python Library for Explaining 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 = {10.1145/3722212.3725125},
url = {https://dl.acm.org/doi/10.1145/3722212.3725125},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 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 |
| 10,679 | SHARQ: Explainability Framework for Association Rules on Relational Data | 2025 | SIGMOD | 5.093636e-05 |
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