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: 5462
Venue: SIGMOD
Year: 2017
Pagerank: 7.457539e-05
Overall Rank: 3,380 | 76.82%
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
1,500	Efficient Discovery of Approximate Dependencies	2018	VLDB	0.00010561098
1,798	SMOKE: Fine-grained Lineage at Interactive Speed	2018	VLDB	9.7361937e-05
3,441	A Statistical Perspective on Discovering Functional Dependencies in Noisy Data	2020	SIGMOD	7.4138323e-05
5,312	Explaining Repaired Data with CFDs	2018	VLDB	6.2698779e-05
8,160	ICARUS: Minimizing Human Effort in Iterative Data Completion	2018	VLDB	5.4754476e-05
8,594	Exploratory Training: When Annotators Learn About Data	2023	SIGMOD	5.4053095e-05
9,177	VerifAI: Verified Generative AI	2024	CIDR	5.3078984e-05
9,923	Efficient Differential Dependency Discovery	2024	VLDB	5.1955087e-05
10,001	Reptile: Aggregation-level Explanations for Hierarchical Data	2022	SIGMOD	5.1814573e-05
10,681	User-Centric Property Graph Repairs	2025	SIGMOD	5.093636e-05
11,069	Versatile Property Graph Transformations	2025	VLDB	5.093636e-05
11,652	Contextual Data Cleaning with Ontology FDs	2021	SIGMOD	5.093636e-05
11,915	Demonstration of Smoke: A Deep Breath of Data-Intensive Lineage Applications	2018	SIGMOD	5.093636e-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
376	Discovering Denial Constraints	2013	VLDB	0.00019677674
647	Discovering Data Quality Rules	2008	VLDB	0.00015334666
714	Guided Data Repair	2011	VLDB	0.00014662041
725	NADEEF: A Commodity Data Cleaning System	2013	SIGMOD	0.00014617251
729	Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms	2015	VLDB	0.00014539421
1,351	Detecting Data Errors: Where are we and what needs to be done?	2016	VLDB	0.00011064851
1,374	Data Profiling with Metanome	2015	VLDB	0.00010986078
2,142	Messing Up with BART: Error Generation for Evaluating Data-Cleaning Algorithms	2016	VLDB	9.0975882e-05
2,365	A Revival of Integrity Constraints for Data Cleaning	2008	VLDB	8.6867205e-05
4,183	Scalable Discovery of Unique Column Combinations	2014	VLDB	6.8467773e-05
4,386	Divide & Conquer-based Inclusion Dependency Discovery	2015	VLDB	6.7309577e-05
9,340	RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets	2016	SIGMOD	5.2869213e-05

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