AbstractAutomatic term recognition (ATR) methods help to identify the most representative terms in a corpus automatically, saving time and allowing managing large amounts of data that could not be dealt with manually. This paper presents the evaluation of two ATR methods implemented on a 2.6 million-word legal corpus designed and compiled ad hoc: Keywords (Scott, 2008) and Chung's method (2003). Both techniques have been assessed as regards precision and recall. The results clearly show that Keywords is, by far, the most efficient one achieving to recognize 62% true terms out of the 2,000 items evaluated in this study
Automatic Term Recognition (ATR) is an important method for the summarization and analysis of large ...
The introduction of legal English as a compulsory subject in the curriculum of the Law Degrees taugh...
International audienceAutomatic terminology processing appeared 10 years ago when electronic corpora...
Automatic Term Recognition focuses on the extraction of words and multi-word expressions that are si...
PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20...
Automatic Term recognition (ATR) is a fundamental processing step preceding more complex tasks such ...
In this paper a machine learning approach is applied to Automatic Term Recognition (ATR). Similar ap...
In this paper, we propose a method for automatic term recognition (ATR) which uses the statistical d...
In any terminological study, candidate term extraction is a very time-consuming task. Corpus analysi...
The use of specialised corpora as support material in ESP/EAP is a widespread phenomenon yet, to the...
Automatic term extraction is a task in the field of natural language processing that aims to automat...
Automated Term Recognition (ATR) is the task of finding terminology from raw text. It involves desig...
The TermEval 2020 shared task provided a platform for researchers to work on automatic term extracti...
The article describes an analysis of automatic term recognition results performed for single- and mu...
Automatic term extraction is a productive field of research within natural language processing, but ...
Automatic Term Recognition (ATR) is an important method for the summarization and analysis of large ...
The introduction of legal English as a compulsory subject in the curriculum of the Law Degrees taugh...
International audienceAutomatic terminology processing appeared 10 years ago when electronic corpora...
Automatic Term Recognition focuses on the extraction of words and multi-word expressions that are si...
PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20...
Automatic Term recognition (ATR) is a fundamental processing step preceding more complex tasks such ...
In this paper a machine learning approach is applied to Automatic Term Recognition (ATR). Similar ap...
In this paper, we propose a method for automatic term recognition (ATR) which uses the statistical d...
In any terminological study, candidate term extraction is a very time-consuming task. Corpus analysi...
The use of specialised corpora as support material in ESP/EAP is a widespread phenomenon yet, to the...
Automatic term extraction is a task in the field of natural language processing that aims to automat...
Automated Term Recognition (ATR) is the task of finding terminology from raw text. It involves desig...
The TermEval 2020 shared task provided a platform for researchers to work on automatic term extracti...
The article describes an analysis of automatic term recognition results performed for single- and mu...
Automatic term extraction is a productive field of research within natural language processing, but ...
Automatic Term Recognition (ATR) is an important method for the summarization and analysis of large ...
The introduction of legal English as a compulsory subject in the curriculum of the Law Degrees taugh...
International audienceAutomatic terminology processing appeared 10 years ago when electronic corpora...