UGuide – User-Guided Discovery of FD-Detectable Errors

Summary: UGuide: end-to-end discovery of FD-detectable errors in dirty data by deriving approximate FDs and flagging suspect cells. With a constrained expert budget, it selects FDs, cells, or tuples to maximize error discovery via efficient interactive algorithms. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h9d8afdc306435663
Venue: SIGMOD
Year: 2017
Pagerank: 7.3120636e-05
Overall Rank: 3,421 | 77.01%
DOI: 10.1145/3035918.3064024

Incoming Non-self Citations Over Time

Authors

1. Saravanan Thirumuruganathan (Hamad Bin Khalifa University; Qatar Computing Research Institute)
2. Laure Berti-Equille (Hamad Bin Khalifa University; Qatar Computing Research Institute)
3. Mourad Ouzzani (Hamad Bin Khalifa University; Qatar Computing Research Institute)
4. Jorge-Arnulfo Quiane-Ruiz (Hamad Bin Khalifa University; Qatar Computing Research Institute)
5. Nan Tang (Hamad Bin Khalifa University; Qatar Computing Research Institute)

BibTeX Citation

@inproceedings{thirumuruganathan_sigmod17,
        title = {{UGuide – User-Guided Discovery of FD-Detectable Errors}},
        author = {Thirumuruganathan, Saravanan and Berti-Equille, Laure and Ouzzani, Mourad and Quiane-Ruiz, Jorge-Arnulfo and Tang, Nan},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3064024},
        url = {https://dl.acm.org/doi/10.1145/3035918.3064024},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,488	Efficient Discovery of Approximate Dependencies	2018	VLDB	0.00010513265
1,713	SMOKE: Fine-grained Lineage at Interactive Speed	2018	VLDB	9.8129981e-05
3,194	A Statistical Perspective on Discovering Functional Dependencies in Noisy Data	2020	SIGMOD	7.5469742e-05
5,395	Explaining Repaired Data with CFDs	2018	VLDB	6.1486851e-05
8,339	ICARUS: Minimizing Human Effort in Iterative Data Completion	2018	VLDB	5.3500594e-05
8,764	Exploratory Training: When Annotators Learn About Data	2023	SIGMOD	5.2815275e-05
9,320	VerifAI: Verified Generative AI	2024	CIDR	5.1941278e-05
10,110	Efficient Differential Dependency Discovery	2024	VLDB	5.0765311e-05
10,191	Reptile: Aggregation-level Explanations for Hierarchical Data	2022	SIGMOD	5.0628015e-05
11,130	User-Centric Property Graph Repairs	2025	SIGMOD	4.9769913e-05
11,434	Versatile Property Graph Transformations	2025	VLDB	4.9769913e-05
11,965	Contextual Data Cleaning with Ontology FDs	2021	SIGMOD	4.9769913e-05
12,220	Demonstration of Smoke: A Deep Breath of Data-Intensive Lineage Applications	2018	SIGMOD	4.9769913e-05

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
350	Discovering Denial Constraints	2013	VLDB	0.00020244085
650	Discovering Data Quality Rules	2008	VLDB	0.00015142855
697	NADEEF: A Commodity Data Cleaning System	2013	SIGMOD	0.00014687805
716	Guided Data Repair	2011	VLDB	0.00014546968
728	Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms	2015	VLDB	0.00014436728
1,344	Detecting Data Errors: Where are we and what needs to be done?	2016	VLDB	0.00010951939
1,394	Data Profiling with Metanome	2015	VLDB	0.00010791559
2,054	Messing Up with BART: Error Generation for Evaluating Data-Cleaning Algorithms	2016	VLDB	9.1158071e-05
2,404	A Revival of Integrity Constraints for Data Cleaning	2008	VLDB	8.5149764e-05
4,226	Scalable Discovery of Unique Column Combinations	2014	VLDB	6.7151469e-05
4,247	Divide & Conquer-based Inclusion Dependency Discovery	2015	VLDB	6.703008e-05
9,529	RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets	2016	SIGMOD	5.1658503e-05

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