Abstract
This paper presents the evaluation of a set of heuristics to improve the quality of extracted terms from an annotated domain corpus written in Portuguese. The proposed heuristics start from part-of-speech and grammatical functional annotation of texts, identifying nouns and noun phrases that are the best candidates to be considered terms of the domain. These nouns and noun phrases are submitted to a set of approximative rules (heuristics) that may either discard some, accept others (removing words or not), or even discover implicit terms that can be inferred. The effectiveness of these heuristics is verified through a corpus experiment, on the basis of a reference list for which usual metrics are computed.
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Lopes, L., Vieira, R. (2012). Improving Portuguese Term Extraction. In: Caseli, H., Villavicencio, A., Teixeira, A., Perdigão, F. (eds) Computational Processing of the Portuguese Language. PROPOR 2012. Lecture Notes in Computer Science(), vol 7243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28885-2_9
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DOI: https://doi.org/10.1007/978-3-642-28885-2_9
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