As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality
phrases from a text corpus and has various downstream applications including information …

Terminology extraction is an essential task in domain knowledge acquisition, as well as for
information retrieval. It is also a mandatory first step aimed at building/enriching …

Text data are ubiquitous and play an essential role in big data applications. However, text
data are mostly unstructured. Transforming unstructured text into structured units (eg …

Automatic term extraction (ATE) is a Natural Language Processing (NLP) task that eases the
effort of manually identifying terms from domain-specific corpora by providing a list of …

A glossary is an important part of any software requirements document. By making explicit
the technical terms in a domain and providing definitions for them, a glossary helps mitigate …

This paper compares different transformer-based language models for automatic term
extraction from agriculture-related texts. Agriculture is an important economic sector faced …

Abstract Automated Term Extraction (ATE), even though well-investigated, continues to be a
challenging task. Approaches conventionally extract terms on corpus or document level and …

Automatic term extraction is a productive field of research within natural language
processing, but it still faces significant obstacles regarding datasets and evaluation, which …

Automatically recognized terminology is widely used for various domain-specific texts
processing tasks, such as machine translation, information retrieval or ontology construction …

In this paper we propose an automatic term extraction approach that uses machine learning
incorporating varied and rich features of candidate terms. In our preliminary experiments, we …