Discovering Top-k Rules using Subjective and Objective Criteria

Summary: Proposes entity-enhancing rules (REEs) and a bi-criteria model that blends objective support and confidence with user-specific subjective criteria learned via active learning for top-k rule discovery. Introduces top-k and any-time lazy-discovery algorithms, parallelizable to reduce runtime with more cores, delivering up to 134x speedups over traditional rule discovery on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6635
Venue: SIGMOD
Year: 2023
Pagerank: 5.271035e-05
Overall Rank: 9,427 | 35.33%
DOI: 10.1145/3588924

Incoming Non-self Citations Over Time

Authors

1. Wenfei Fan (Beihang University; Shenzhen University; University of Edinburgh)
2. Ziyan Han (Beihang University)
3. Yaoshu Wang (Shenzhen University)
4. Min Xie (Shenzhen University)

BibTeX Citation

@inproceedings{fan_sigmod23,
        title = {{Discovering Top-k Rules using Subjective and Objective Criteria}},
        author = {Fan, Wenfei and Han, Ziyan and Wang, Yaoshu and Xie, Min},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588924},
        url = {https://dl.acm.org/doi/10.1145/3588924},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,647	Rock: Cleaning Data by Embedding ML in Logic Rules	2024	SIGMOD	5.2430158e-05
9,923	Efficient Differential Dependency Discovery	2024	VLDB	5.1955087e-05
9,997	HyperBlocker: Accelerating Rule-based Blocking in Entity Resolution using GPUs	2025	VLDB	5.1814573e-05
9,999	Discovering Top-k Relevant and Diversified Rules	2024	SIGMOD	5.1814573e-05
10,606	Efficient Partition-based Approaches for Diversified Top-k Subgraph Matching	2026	VLDB	5.093636e-05
10,766	Incremental Rule Discovery in Response to Parameter Updates	2025	SIGMOD	5.093636e-05
11,317	Rock: Cleaning Data with both ML and Logic Rules	2024	VLDB	5.093636e-05
11,424	Splitting Tuples of Mismatched Entities	2023	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
33	Consistent Query Answers in Inconsistent Databases	1999	PODS	0.00049907763
112	HoloClean: Holistic Data Repairs with Probabilistic Inference	2017	VLDB	0.00032801121
161	Mining Frequent Patterns without Candidate Generation	2000	SIGMOD	0.00027981772
176	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00027191081
376	Discovering Denial Constraints	2013	VLDB	0.00019677674
489	Distributed Representations of Tuples for Entity Resolution	2018	VLDB	0.0001761456
618	A Hybrid Approach to Functional Dependency Discovery	2016	SIGMOD	0.00015711835
704	Dynamic Itemset Counting and Implication Rules for Market Basket Data	1997	SIGMOD	0.00014837704
729	Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms	2015	VLDB	0.00014539421
946	HoloDetect: Few-Shot Learning for Error Detection	2019	SIGMOD	0.00013054126
1,033	On Generating Near-Optimal Tableaux for Conditional Functional Dependencies	2008	VLDB	0.00012529852
1,465	Synthesizing Entity Matching Rules by Examples	2018	VLDB	0.00010689571
1,500	Efficient Discovery of Approximate Dependencies	2018	VLDB	0.00010561098
1,741	Efficient Denial Constraint Discovery with Hydra	2018	VLDB	9.8755846e-05
2,290	ZeroER: Entity Resolution using Zero Labeled Examples	2020	SIGMOD	8.799251e-05
2,297	Raha: A Configuration-Free Error Detection System	2019	SIGMOD	8.7897221e-05
2,475	Deep Learning for Blocking in Entity Matching: A Design Space Exploration	2021	VLDB	8.5277654e-05
2,685	Approximate Denial Constraints	2020	VLDB	8.2594662e-05
3,441	A Statistical Perspective on Discovering Functional Dependencies in Noisy Data	2020	SIGMOD	7.4138323e-05
3,715	SLiMFast: Guaranteed Results for Data Fusion and Source Reliability	2017	SIGMOD	7.1763559e-05
4,023	Smurf: Self-Service String Matching Using Random Forests	2019	VLDB	6.949387e-05
4,832	Association Rules with Graph Patterns	2015	VLDB	6.4877e-05
5,052	Distributed implementations of dependency discovery algorithms	2019	VLDB	6.3846183e-05
5,391	MDedup: Duplicate Detection with Matching Dependencies	2020	VLDB	6.2343031e-05
6,403	Parallel Discrepancy Detection and Incremental Detection	2021	VLDB	5.8859374e-05
10,111	Parallel Rule Discovery from Large Datasets by Sampling	2022	SIGMOD	5.1347137e-05

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