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Pre-trained Embeddings for Entity Resolution: An Experimental Analysis

Summary: Thorough empirical study of 12 pre-trained embeddings (fastText, BERT variants) on 17 ER benchmarks, measuring vectorization cost, blocking scalability vs a SOTA deep blocker, and supervised/unsupervised matching performance. Provides actionable insights on encoding vs accuracy trade-offs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13074
Venue
VLDB
Year
2023
Pagerank
5.0060112e-05
Overall Rank
6,558 | 54.43%
DOI
10.14778/3598581.3598594

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