Linked Life Data

10857671

Source:http://linkedlifedata.com/resource/pubmed/id/10857671

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-3
pubmed:dateCreated
2000-8-23
pubmed:abstractText
This paper reports a new approach to estimating the extent to which words have predominant noun and verb usages which do not require human judgments about parts of speech. The Hyperspace Analog to Language model (HAL, Lund & Burgess, 1996) was used to computationally estimate noun vs verb usage based on the statistical regularities present in a large-scale electronic text corpus. This measure can be used to estimate the extent to which a given word occurs in typical noun or verb sentence contexts (i.e., its distributional typicality) in informal contemporary discourse.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0278-2626
pubmed:author
pubmed:issnType
Print
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
94-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Distributional typicality: a new approach to estimating noun and verb usage from large scale text corpora.
pubmed:affiliation
University of California, Riverside, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.