Multi-unit association measures: Moving beyond pairs of words (2018)
AuthorsDunn Jshow all
This paper formulates and evaluates a series of multi-unit measures of directional association, building on the pairwise ΔP measure, that are able to quantify association in sequences of varying length and type of representation. Multi-unit measures face an additional segmentation problem: once the implicit length constraint of pairwise measures is abandoned, association measures must also identify the borders of meaningful sequences. This paper takes a vector-based approach to the segmentation problem by using 18 unique measures to describe different aspects of multi-unit association. An examination of these measures across eight languages shows that they are stable across languages and that each provides a unique rank of associated sequences. Taken together, these measures expand corpus-based approaches to association by generalizing across varying lengths and types of representation.
CitationDunn J (2018). Multi-unit association measures: Moving beyond pairs of words. International Journal of Corpus Linguistics. 23(2). 183-215.
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Keywordsassociation strength; multi-unit association; sequences; ΔP; collocations
ANZSRC Fields of Research20 - Language, Communication and Culture::2004 - Linguistics::200408 - Linguistic Structures (incl. Grammar, Phonology, Lexicon, Semantics)
20 - Language, Communication and Culture::2004 - Linguistics::200402 - Computational Linguistics
20 - Language, Communication and Culture::2003 - Language Studies::200322 - Comparative Language Studies