Using machine learning to perform automatic term recognition
2010 (English)In: Proceedings of the LREC 2010 Workshop on Methods for automatic acquisition of Language Resources and their evaluation methods / [ed] Núria Bel, Béatrice Daille, Andrejs Vasiljevs, 2010, 49-54 p.Conference paper (Refereed)
In this paper a machine learning approach is applied to Automatic Term Recognition (ATR). Similar approaches have been successfully used in Automatic Keyword Extraction (AKE). Using a dataset consisting of Swedish patent texts and validated terms belonging to these texts, unigrams and bigrams are extracted and annotated with linguistic and statistical feature values. Experiments using a varying ratio between positive and negative examples in the training data are conducted using the annotated n-grams. The results indicate that a machine learning approach is viable for ATR. Furthermore, a machine learning approach for bilingual ATR is discussed. Preliminary analysis however indicate that some modifications have to be made to apply the monolingual machine learning approach to a bilingual context.
Place, publisher, year, edition, pages
2010. 49-54 p.
Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:liu:diva-75237ISI: 000356879501100OAI: oai:DiVA.org:liu-75237DiVA: diva2:505121
LREC 2010 Workshop on Methods for automatic acquisition of Language Resources and their evaluation methods, 23 May 2010, Valletta, Malta