Multi-unit association measures: Moving beyond pairs of words

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dc.contributor.authorDunn J
dc.date.accessioned2019-09-17T01:59:44Z
dc.date.available2019-09-17T01:59:44Z
dc.date.issued2018en
dc.date.updated2019-07-22T23:24:44Z
dc.description.abstractThis 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.en
dc.identifier.citationDunn J (2018). Multi-unit association measures: Moving beyond pairs of words. International Journal of Corpus Linguistics. 23(2). 183-215.en
dc.identifier.doihttps://doi.org/10.1075/ijcl.16098.dun
dc.identifier.urihttp://hdl.handle.net/10092/17133
dc.language.isoen
dc.subjectassociation strengthen
dc.subjectmulti-unit associationen
dc.subjectsequencesen
dc.subjectΔPen
dc.subjectcollocationsen
dc.subject.anzsrcFields of Research::47 - Language, communication and culture::4704 - Linguistics::470409 - Linguistic structures (incl. phonology, morphology and syntax)en
dc.subject.anzsrcField of Research::20 - Language, Communication and Culture::2004 - Linguistics::200402 - Computational Linguisticsen
dc.subject.anzsrcFields of Research::47 - Language, communication and culture::4703 - Language studies::470304 - Comparative language studiesen
dc.titleMulti-unit association measures: Moving beyond pairs of wordsen
dc.typeJournal Articleen
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