Publication Date
2-10-2016
Subjects
Classification, Automatic indexing, Thesauri, Library automation, Technological change
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.
Recommended Citation
Mitchell, P., Grimston, T., & Parkes, R. (2016). Introducing an automated subject classifier. VALA. https://research.acer.edu.au/information_management/3
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright Statement
Copyright 2016 Australian Council for Educational Research. This work is licensed under a Creative Commons Attribution-NonCommercial License.
Place of Publication
Melbourne
Publisher
VALA
Geographic Subject
Victoria
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.