Automated Language Identification of Bibliographic Resources. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Morris, Victoria
• Is Part Of: Cataloging & classification quarterly. Volume 58:Issue 1(2020)
• Page Start: 1
• Page End: 27
• Publication Date: 2020-01-02
• Subjects: Language identification -- machine learning -- automatic metadata generation -- metadata -- legacy record enhancement; Cataloging -- Periodicals; Classification -- Books -- Periodicals; 025.3
• DOI: 10.1080/01639374.2019.1700201
• Languages: English
• ISSNs: 0163-9374

Abstract

Abstract: This article describes experiments in the use of machine learning techniques at the British Library to assign language codes to catalog records, in order to provide information about the language of content of the resources described. In the first phase of the project, language codes were assigned to 1.15 million records with 99.7% confidence. The automated language identification tools developed will be used to contribute to future enhancement of over 4 million legacy records.