Conference paper
My Word! Machine versus Human versus Computation Methods for Identifying and Resolving Acronyms
Computación y Sistemas, Vol.23(3)
International Conference on Computational Linguistics and Intelligent Text Processing, 20 (2019–2019)
2019
DOI: 10.13053/CyS-23-3-3249
Abstract
Acronyms are commonly used in human language as alternative forms of concepts to increase recognition, to reduce duplicate references to the same concept, and to stress important concepts. There are no standard rules for acronym creation; therefore, both machine-based acronym identification and acronym resolution are highly prone to error. This might be resolved by a human computation approach, which can take advantage of knowledge external to the document collection. Using three text collections with different properties, we compare a machine-based algorithm with a crowdsourcing approach to identify acronyms. We then perform acronym resolution using these two approaches, plus a game-based approach. The crowd and game-based methods outperform the machine algorithm, even when external information is not used. Also,crowd and game formats offered similar performance with a difference in cost.
Details
- Title: Subtitle
- My Word! Machine versus Human versus Computation Methods for Identifying and Resolving Acronyms
- Creators
- Christopher G Harris - University of IowaPadmini Srinivasan - University of Iowa, Computer Science
- Resource Type
- Conference paper
- Publication Details
- Computación y Sistemas, Vol.23(3)
- Conference
- International Conference on Computational Linguistics and Intelligent Text Processing, 20 (2019–2019)
- DOI
- 10.13053/CyS-23-3-3249
- ISSN
- 2007-9737
- Number of pages
- 893–904
- Language
- English
- Date published
- 2019
- Academic Unit
- Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984006764302771
Metrics
23 Record Views