January 21, 2021

Journal Article: “Annif: DIY Automated Subject Indexing Using Multiple Algorithms”

Title

Annif: DIY Automated Subject Indexing Using Multiple Algorithms

Author

Osma Suominen
National Library of Finland

Source

LIBER Quarterly
The Journal of the European Association of Research Libraries
29.1 (2019)

Abstract

Manually indexing documents for subject-based access is a labour-intensive process. We propose using metadata gathered from bibliographic databases to train algorithms that assist librarians in that work. We have developed Annif, an open source tool and microservice for automated subject indexing. After training it with a subject vocabulary and existing metadata, Annif can be used to assign subject headings for new documents. We have tested Annif with different document collections including scientific papers, old scanned books and contemporary e-books, Q&A pairs from an “ask a librarian” service, Finnish Wikipedia, and the archives of a local newspaper. The results of analysing scientific papers and current books have been reassuring, while other types of documents have proved to be more challenging. The current version is based on a combination of existing natural language processing and machine learning tools. By combining multiple approaches and existing open source algorithms, Annif can build on the strengths of individual algorithms and adapt to different settings. With Annif, we expect to improve subject indexing and classification processes especially for electronic documents as well as collections that otherwise would not be indexed at all.

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About Gary Price

Gary Price (gprice@mediasourceinc.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. Before launching INFOdocket, Price and Shirl Kennedy were the founders and senior editors at ResourceShelf and DocuTicker for 10 years. From 2006-2009 he was Director of Online Information Services at Ask.com, and is currently a contributing editor at Search Engine Land.

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