Providing pin-point page-level precision to 1 trillion tokens of text for workset creation

Bainbridge, David; Downie, J. Stephen; Capitanu, Boris

doi:10.1145/3197026.3203875

Files

p407-bainbridge.pdf

Published version, 968.4Kb

DOI

10.1145/3197026.3203875

Citation

Export citation

Bainbridge, D., Downie, J. S., & Capitanu, B. (2018). Providing pin-point page-level precision to 1 trillion tokens of text for workset creation. In Proceedings of 18th ACM/IEEE Joint Conference on Digital Libraries (JCDL 2018) (pp. 407–408). New York, USA: ACM. https://doi.org/10.1145/3197026.3203875

Permanent Research Commons link: https://hdl.handle.net/10289/11929

Abstract

We report on the work undertaken developing a web environment that allows users to search over 1 trillion tokens of text -- down to the page-level -- of the HathiTrust Part-of-Speech Extracted Features Dataset to help produce worksets for scholarly analysis. We present an extended example of the web environment in use, along with details about its implementation.

Date

2018

Type

Conference Contribution

Publisher

ACM

Rights

Collections

Computing and Mathematical Sciences Papers [1217]