  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 delimited,
sentence splitted, lower-cased, well-balanced, representative, 10-million-word
corpus of Turkish.
