Abstract
Studies of different term extractors on a corpus of the biomedical domain revealed decreasing performances when applied to highly technical texts. Facing the difficulty or impossibility to customize existing tools, we developed a tunable term extractor. It exploits linguistic-based rules in combination with the reuse of existing terminologies, i.e. exogenous disambiguation. Experiments reported here show that the combination of the two strategies allows the extraction of a greater number of term candidates with a higher level of reliability. We further describe the extraction process involving both endogenous and exogenous disambiguation implemented in the term extractor \(\rm Y\kern-.36em \lower.7ex\hbox{A}\kern-.25em T\kern-.1667em\lower.7ex\hbox{E}\kern-.08emA\).
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Aubin, S., Hamon, T. (2006). Improving Term Extraction with Terminological Resources. In: Salakoski, T., Ginter, F., Pyysalo, S., Pahikkala, T. (eds) Advances in Natural Language Processing. FinTAL 2006. Lecture Notes in Computer Science(), vol 4139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816508_39
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DOI: https://doi.org/10.1007/11816508_39
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