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. © 2012 Springer-Verlag.
CITATION STYLE
Lopes, L., & Vieira, R. (2012). Improving Portuguese term extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7243 LNAI, pp. 85–92). https://doi.org/10.1007/978-3-642-28885-2_9
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