ATA – Automatic Term Acquisition

Terminological acquisition is an important issue when learning about Natural Language Processing (NLP) due to the constant terminological renewal caused by technological changes. Terms play a key role in several NLP activities such as machine translation, automatic indexing, text understanding, and information retrieval. This is especially true at this time when corpora in electronic format keep growing in number and variety. In this work we start by using morphological and syntactic information to locate candidate noun phrases, and then we use statistical information to improve result accuracy.