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Efficient record linkage for large datasets by business names / by Hanan Ather, Serge Godbout, and Dave MacNeil.: CS11-522/2024-1-19E-PDF

"Accurate and efficient record linkage is crucial for maintaining a comprehensive and current Statistical Business Register (SBR) at Statistics Canada. Linking external business lists to the SBR by name presents computational and methodological challenges, especially as data volumes grow. This paper describes a scalable methodology that employs blocking techniques to constrain the computational search space and integrates multiple similarity measures - from edit distances and n-gram overlaps to embedding-based methods using Sentence-BERT (SBERT) - to identify likely matches. By combining simple character-level comparisons with more advanced semantic embedding methods, the approach can adapt to various naming conventions and complexities. While it does not guarantee superior accuracy in all circumstances, it offers a pragmatic balance between computational feasibility and linkage quality"--Abstract, page [2].

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.966663&sl=0

Publication information
Department/Agency
  • Statistics Canada, issuing body.
TitleEfficient record linkage for large datasets by business names / by Hanan Ather, Serge Godbout, and Dave MacNeil.
Variant title
  • At head of title: Proceedings of Statistics Canada Symposium 2024 : the future of official statistics
Series title
  • [Statistics Canada international symposium series : proceedings], 1709-8211
Publication typeMonograph - View Master Record
Language[English]
Other language editions[French]
FormatDigital text
Electronic document
Note(s)
  • Title from cover.
  • Issued also in French under title: Couplage efficace d'enregistrements pour les grands ensembles de données, selon les noms d'entreprise.
  • Includes bibliographical references.
Publishing information
  • [Ottawa] : Statistics Canada = Statistique Canada, September 8, 2025.
Author / Contributor
  • Ather, Hanan, author.
Description1 online resource (8 unnumbered pages).
Catalogue number
  • CS11-522/2024-1-19E-PDF
Departmental catalogue number11-522-X
Subject terms
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