Towards Interpretable and Learnable Risk Analysis for Entity Resolution

Summary: Proposes an interpretable, learnable risk-analysis framework for entity resolution that ranks labeled pairs by mislabeling risk. Automatically derives interpretable risk features and trains a learnable model; experiments show higher accuracy than baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h13a72ee1285363a2
Venue: SIGMOD
Year: 2020
Pagerank: 5.0334833e-05
Overall Rank: 10,280 | 31.10%
DOI: 10.1145/3318464.3380572

Incoming Non-self Citations Over Time

Authors

1. Zhaoqiang Chen (Northwestern Polytechnical University)
2. Qun Chen (Northwestern Polytechnical University)
3. Boyi Hou (Northwestern Polytechnical University)
4. Zhanhuai Li (Northwestern Polytechnical University)
5. Guoliang Li (Tsinghua University)

BibTeX Citation

@inproceedings{chen_sigmod20,
        title = {{Towards Interpretable and Learnable Risk Analysis for Entity Resolution}},
        author = {Chen, Zhaoqiang and Chen, Qun and Hou, Boyi and Li, Zhanhuai and Li, Guoliang},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3380572},
        url = {https://dl.acm.org/doi/10.1145/3318464.3380572},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,788	Splitting Tuples of Mismatched Entities	2023	SIGMOD	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
100	HoloClean: Holistic Data Repairs with Probabilistic Inference	2017	VLDB	0.00033951027
158	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028049555
199	CrowdER: Crowdsourcing Entity Resolution	2012	VLDB	0.0002551523
434	Corleone: Hands-Off Crowdsourcing for Entity Matching	2014	SIGMOD	0.00018323777
459	Distributed Representations of Tuples for Entity Resolution	2018	VLDB	0.00017863654
535	On Active Learning of Record Matching Packages	2010	SIGMOD	0.00016768308
619	Reasoning about Record Matching Rules	2009	VLDB	0.00015503747
621	Entity Resolution: Theory, Practice & Open Challenges	2012	VLDB	0.00015460277
932	Question Selection for Crowd Entity Resolution	2013	VLDB	0.00012981731
1,099	KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing	2015	SIGMOD	0.00012008783
1,473	Crowdsourcing Algorithms for Entity Resolution	2014	VLDB	0.0001052886
2,641	Progressive Approach to Relational Entity Resolution	2014	VLDB	8.1723025e-05
2,647	Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning	2015	VLDB	8.1565673e-05
3,414	Waldo: An Adaptive Human Interface for Crowd Entity Resolution	2017	SIGMOD	7.3058225e-05
3,672	Online Entity Resolution Using an Oracle	2016	VLDB	7.0926043e-05
3,680	Generating Concise Entity Matching Rules	2017	SIGMOD	7.0846793e-05
4,074	Crowd-Based Deduplication: An Adaptive Approach	2015	SIGMOD	6.8062505e-05
4,626	Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach	2016	SIGMOD	6.480594e-05
6,404	Human-in-the-loop Data Integration	2017	VLDB	5.7797097e-05
7,074	Cost-Effective Data Annotation using Game-Based Crowdsourcing	2019	VLDB	5.5915502e-05

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8	2,271	ZeroER: Entity Resolution using Zero Labeled Examples	2020	SIGMOD
9	7,601	Robust Entity Resolution using Random Graphs	2018	SIGMOD
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