Associative Measures and Multi-word Unit Extraction in Turkish
Journal Title: Mersin Üniversitesi Dil ve Edebiyat Dergisi - Year 2015, Vol 12, Issue 1
Abstract
Associative measures are “mathematical formulas determining the strength of association between two or more words based on their occurrences and cooccurrences in a text corpus” (Pecina, 2010, p. 138). The purpose of this paper is to test the 12 associative measures that Text-NSP (Banerjee & Pedersen, 2003) contains on a 10-million-word subcorpus of Turkish National Corpus (TNC) (Aksan et.al., 2012). A statistical comparison of those measures is out of the scope of the study, and the measures will be evaluated according to the linguistic relevance of the rankings they provide. The focus of the study is basically on optimizing the corpus data, before applying the measures and then, evaluating the rankings produced by these measures as a whole, not on the linguistic relevance of individual n-grams. The findings include intra-linguistically relevant associative measures for a comma representative, 10-million-word corpus of Turkish. splitted, delimited, sentence lower-cased, well-balanced
Authors and Affiliations
Ümit Mersinli
Keywords
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