Dual-Objective Fine-Tuning of BERT for Entity Matching

Summary: JointBERT dual-objective fine-tuning for entity matching: binary match and multi-class identifier prediction under partial identifier coverage. With ample data, it yields 1–5% F1 gains on seen products over single-objective BERT, but falters on unseen products; LIME-based analysis highlights emphasis on informative word classes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12374
Venue: VLDB
Year: 2021
Pagerank: 5.4544359e-05
Overall Rank: 5,533 | 61.51%
DOI: 10.14778/3467861.3467878

Incoming Non-self Citations Over Time

Authors

1. Ralph Peeters
2. Christian Bizer

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,711	Analyzing How BERT Performs Entity Matching	2022	VLDB	4.9517546e-05
7,052	Pre-trained Embeddings for Entity Resolution: An Experimental Analysis	2023	VLDB	4.8497453e-05
8,958	FlexER: Flexible Entity Resolution for Multiple Intents	2023	SIGMOD	4.4210635e-05
9,460	The Battleship Approach to the Low Resource Entity Matching Problem	2023	SIGMOD	4.3366491e-05
10,022	In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration	2026	SIGMOD	4.1945683e-05
11,047	Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution	2024	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
221	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.00033121824
300	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028441466
712	Magellan: Toward Building Entity Matching Management Systems	2016	VLDB	0.00017732426
754	Distributed Representations of Tuples for Entity Resolution	2018	VLDB	0.00017117211

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
300	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028441466
9,460	The Battleship Approach to the Low Resource Entity Matching Problem	2023	SIGMOD	4.3366491e-05
319	Evaluation of entity resolution approaches on real-world match problems	2010	VLDB	0.00027781866
4,837	Entity Resolution with Hierarchical Graph Attention Networks	2022	SIGMOD	5.8892326e-05
3,640	Deep Learning for Blocking in Entity Matching: A Design Space Exploration	2021	VLDB	6.8891671e-05
2,767	A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching	2020	SIGMOD	8.1513883e-05
7,052	Pre-trained Embeddings for Entity Resolution: An Experimental Analysis	2023	VLDB	4.8497453e-05
11,047	Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution	2024	VLDB	4.1945683e-05
221	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.00033121824
6,711	Analyzing How BERT Performs Entity Matching	2022	VLDB	4.9517546e-05