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Titolo:
Distributional typicality: A new approach to estimating noun and verb usage from large scale text corpora
Autore:
Chiarello, C; Shears, C; Lund, K;
Indirizzi:
Univ Calif Riverside, Riverside, CA 92521 USA Univ Calif Riverside Riverside CA USA 92521 side, Riverside, CA 92521 USA
Titolo Testata:
BRAIN AND COGNITION
fascicolo: 1-3, volume: 43, anno: 2000,
pagine: 94 - 98
SICI:
0278-2626(200006/08)43:1-3<94:DTANAT>2.0.ZU;2-E
Fonte:
ISI
Lingua:
ENG
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Life Sciences
Citazioni:
9
Recensione:
Indirizzi per estratti:
Indirizzo: Chiarello, C Univ Calif Riverside, Riverside, CA 92521 USA Univ Calif Riverside Riverside CA USA 92521 de, CA 92521 USA
Citazione:
C. Chiarello et al., "Distributional typicality: A new approach to estimating noun and verb usage from large scale text corpora", BRAIN COGN, 43(1-3), 2000, pp. 94-98

Abstract

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 Br 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, (C) 2000 Academic Press.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 30/03/20 alle ore 13:25:41