Document Type
Article
Abstract
This article describes multiple experiments in text mining at Northern Illinois University that were undertaken to improve the efficiency and accuracy of cataloging. It focuses narrowly on subject analysis of dime novels, a format of inexpensive fiction that was popular in the United States between 1860 and 1915. NIU holds more than 55,000 dime novels in its collections, which it is in the process of comprehensively digitizing. Classification, keyword extraction, named-entity recognition, clustering, and topic modeling are discussed as means of assigning subject headings to improve their discoverability by researchers and to increase the productivity of digitization workflows.
Publication Date
9-23-2019
Recommended Citation
This is an Accepted Manuscript of an article published by Taylor & Francis in Cataloging & Classification Quarterly on 23/09/2019, available online: http://www.tandfonline.com/10.1080/01639374.2019.1653413.
Original Citation
This is an Accepted Manuscript of an article published by Taylor & Francis in Cataloging & Classification Quarterly on 23/09/2019, available online: http://www.tandfonline.com/10.1080/01639374.2019.1653413.
Department
University Libraries
Legacy Department
Other
ISSN
1544-4554
Language
eng
Publisher
Taylor & Francis
