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: 5.0501823e-05
Overall Rank: 10,250 | 31.11%
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
11,744	Splitting Tuples of Mismatched Entities	2023	SIGMOD	4.9769913e-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
104	HoloClean: Holistic Data Repairs with Probabilistic Inference	2017	VLDB	0.00033676943
158	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028038831
198	CrowdER: Crowdsourcing Entity Resolution	2012	VLDB	0.00025546182
433	Corleone: Hands-Off Crowdsourcing for Entity Matching	2014	SIGMOD	0.00018324965
457	Distributed Representations of Tuples for Entity Resolution	2018	VLDB	0.00017899824
534	On Active Learning of Record Matching Packages	2010	SIGMOD	0.00016799
618	Reasoning about Record Matching Rules	2009	VLDB	0.0001553004
623	Entity Resolution: Theory, Practice & Open Challenges	2012	VLDB	0.00015477107
934	Question Selection for Crowd Entity Resolution	2013	VLDB	0.00012998402
1,098	KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing	2015	SIGMOD	0.00012031983
1,472	Crowdsourcing Algorithms for Entity Resolution	2014	VLDB	0.00010553304
2,643	Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning	2015	VLDB	8.1741373e-05
2,645	Progressive Approach to Relational Entity Resolution	2014	VLDB	8.173459e-05
3,409	Waldo: An Adaptive Human Interface for Crowd Entity Resolution	2017	SIGMOD	7.3230153e-05
3,666	Online Entity Resolution Using an Oracle	2016	VLDB	7.1151622e-05
3,684	Generating Concise Entity Matching Rules	2017	SIGMOD	7.0983735e-05
4,053	Crowd-Based Deduplication: An Adaptive Approach	2015	SIGMOD	6.8253348e-05
4,625	Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach	2016	SIGMOD	6.4948389e-05
6,400	Human-in-the-loop Data Integration	2017	VLDB	5.7962311e-05
7,054	Cost-Effective Data Annotation using Game-Based Crowdsourcing	2019	VLDB	5.6101007e-05

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