Multi-word term extraction from comparable corpora by combining contextual and constituent clues - Ljubešić, Nikola, informatičar (Array, 2012)
In this paper we present an approach to automatically extract and align multi-word terms from an English-Slovene comparable health corpus. First, the terms are extracted from the corpus for each language separately using a list of user-adjustable morphosyntactic patterns and a term weighting measure. Then, the extracted terms are aligned in a bag-of-equivalents fashion with a seed bilingual lexicon. In the extension of the approach we also show that the small general seed lexicon can be enriched with domain-specific vocabulary by harvesting it directly from the comparable corpus, which significantly improves the results of multi-word term mapping. While most previous efforts in bilingual lexicon extraction from comparable corpora have focused on mapping of single words, the proposed technique successfully augments them in that it is able to deal with multi-word terms as well. Since the proposed approach requires minimal knowledge resources, it is easily adaptable for a new language pair or domain, which is one of its biggest advantages.