The use of terms from corpora to better selection term candidates extracted automatically
What is it about?
The identification of reliable terms from domain-specific corpora using computational methods is a task that has to be validated manually by specialists, which is a highly time-consuming activity. To reduce this effort and improve term candidate selection, we implemented the Token Slot Recognition method, a filtering method based on terminological tokens which is used to rank extracted term candidates from domain-specific corpora. This paper presents the implementation of the term candidates filtering method we developed in linguistic and statistical approaches applied for automatic term extraction using several domain-specific corpora in different languages. We observed that the filtering method outperforms term candidate selection by ranking a higher number of terms at the top of the term candidate list than raw frequency. Our analyses further revealed a reduction in the number of term candidates to be validated manually by specialists.
Why is it important?
The paper is important because the number of term candidates extracted automatically from domain-specific corpora has been reduced significantly using the Token Slot Recognition filtering method, so term candidates can be easily and quickly validated by specialists.