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Erschienen in:
2009 | OriginalPaper | Buchkapitel
An Improved Automatic Term Recognition Method for Spanish
verfasst von : Alberto Barrón-Cedeño, Gerardo Sierra, Patrick Drouin, Sophia Ananiadou
Erschienen in: Computational Linguistics and Intelligent Text Processing
Verlag: Springer Berlin Heidelberg
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The
$C\mbox{-}value/NC\mbox{-}value$
algorithm, a hybrid approach to automatic term recognition, has been originally developed to extract multiword term candidates from specialised documents written in English. Here, we present three main modifications to this algorithm that affect how the obtained output is refined. The first modification aims to maximise the number of real terms in the list of candidates with a new approach for the stop-list application process. The second modification adapts the
$C\mbox{-}value$
calculation formula in order to consider single word terms. The third modification changes how the term candidates are grouped, exploiting a lemmatised version of the input corpus. Additionally, size of candidate’s context window is variable. We also show the necessary linguistic modifications to apply this algorithm to the recognition of term candidates in Spanish.