Abstract: The aim of this paper is to evaluate performance of several automatic term extraction methods which can be easily utilized by translators themselves. The experiments are conducted on German newspaper articles in the domain of politics on the topic of Brexit. However, they can be easily replicated on any other topic or language as long as it is supported by all three tools used. The paper first provides an extensive introduction into the field of automatic terminology extraction. Next, selected terminology extraction methods are assessed using precision with respect to the gold standard compiled on the same corpus. Moreover, the corpus has been completely annotated to allow for the calculation of recall. The effects of using five cut-off points are examined in order to find an optimal value which should be used in translation practice.

Marija Brkic Bakaric, Nikola Babic and Maja Matetic, “Application-based Evaluation of Automatic Terminology Extraction” International Journal of Advanced Computer Science and Applications(IJACSA), 12(1), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120103

@article{Bakaric2021,
title = {Application-based Evaluation of Automatic Terminology Extraction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120103},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120103},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {1},
author = {Marija Brkic Bakaric and Nikola Babic and Maja Matetic}
}