MDedup: Duplicate Detection with Matching Dependencies

Summary: MDedup performs fully automatic, rule-based duplicate detection by discovering matching dependencies and learning which to select using dataset features and gold standards. A boosting step improves MD recall, achieving up to 94% F-measure and 100% precision without domain-specific configuration. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: h35fdc7174a6c17ff
Venue: VLDB
Year: 2020
Pagerank: 6.0956156e-05
Overall Rank: 5,522 | 62.88%
DOI: 10.14778/3377369.3377379

Incoming Non-self Citations Over Time

Authors

1. Ioannis Koumarelas (Hasso Plattner Institute; University of Potsdam)
2. Thorsten Papenbrock (Hasso Plattner Institute; University of Potsdam)
3. Felix Naumann (Hasso Plattner Institute; University of Potsdam)

BibTeX Citation

@article{koumarelas_vldb20,
        title = {{MDedup: Duplicate Detection with Matching Dependencies}},
        author = {Koumarelas, Ioannis and Papenbrock, Thorsten and Naumann, Felix},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {5},
        pages = {712--725},
        doi = {10.14778/3377369.3377379},
        url = {https://doi.org/10.14778/3377369.3377379},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,676	Entity Resolution with Hierarchical Graph Attention Networks	2022	SIGMOD	6.4745561e-05
5,076	Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond	2021	SIGMOD	6.2860582e-05
7,875	Learning Over Dirty Data Without Cleaning	2020	SIGMOD	5.4355826e-05
9,565	Deduplicated Sampling On-Demand	2025	VLDB	5.1571823e-05
9,608	Discovering Top-k Rules using Subjective and Objective Criteria	2023	SIGMOD	5.1527671e-05
10,106	Efficient Differential Dependency Discovery	2024	VLDB	5.0789354e-05
10,186	Discovering Top-k Relevant and Diversified Rules	2024	SIGMOD	5.0651993e-05
10,339	Parallel Rule Discovery from Large Datasets by Sampling	2022	SIGMOD	5.0195045e-05
11,188	Incremental Rule Discovery in Response to Parameter Updates	2025	SIGMOD	4.9793485e-05
11,590	Enriching Relations with Additional Attributes for ER	2024	VLDB	4.9793485e-05
11,738	Splitting Tuples of Mismatched Entities	2023	SIGMOD	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
158	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028046388
205	Snorkel: Rapid Training Data Creation with Weak Supervision	2018	VLDB	0.00025181304
457	Distributed Representations of Tuples for Entity Resolution	2018	VLDB	0.00017907103
500	Dependencies Revisited for Improving Data Quality	2008	PODS	0.00017280722
763	AJAX: An Extensible Data Cleaning Tool	2000	SIGMOD	0.00014140127
1,247	Entity Matching: How Similar Is Similar	2011	VLDB	0.00011346515
1,493	Synthesizing Entity Matching Rules by Examples	2018	VLDB	0.00010505174
2,675	The return of JedAI: End-to-End Entity Resolution for Structured and Semi-Structured Data	2018	VLDB	8.1475005e-05

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#	Overall Rank	Paper	Year	Venue
1	9,806	Making It Tractable to Catch Duplicates and Conflicts in Graphs	2023	SIGMOD
2	2,461	Leveraging Aggregate Constraints For Deduplication	2007	SIGMOD
3	134	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB
4	7,068	How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses	2024	VLDB
5	2,555	DogmatiX Tracks down Duplicates in XML	2005	SIGMOD
6	4,051	Crowd-Based Deduplication: An Adaptive Approach	2015	SIGMOD
7	5,849	Industry-Scale Duplicate Detection	2008	VLDB
8	885	Framework for Evaluating Clustering Algorithms in Duplicate Detection	2009	VLDB
9	3,426	Modeling and Querying Possible Repairs in Duplicate Detection	2009	VLDB
10	307	Eliminating Fuzzy Duplicates in Data Warehouses	2002	VLDB