Publication Date

2-10-2016

Subjects

Classification, Automatic indexing, Thesauri, Library automation, Technological change

Comments

This paper was presented at the VALA2016 18th Biennial Conference and Exhibition held at the Melbourne Convention and Exhibition Centre, Melbourne, Australia from 9 - 11 February 2016.

Abstract

The library community understands the value of controlled vocabularies in enhancing resource discovery. There is however ongoing tension between that value and the cost of maintaining and applying specialist vocabularies. This paper presents the outcomes of a 2014-15 trial of automated subject indexing at the Australian Council for Educational Research. The integration of a machine learning classification tool has resulted in streamlined workflows and increased use of machine-readable data. Insights were gained into the decisions human indexers make in using a controlled vocabulary, and into the importance of quality abstracts and metadata.

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Place of Publication

Melbourne

Publisher

VALA

Geographic Subject

Victoria

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