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Euclidean distance between syntactically linked words
Ferrer i Cancho, Ramon
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004-11, Vol.70 (5 Pt 2), p.056135-056135, Article 056135
United States
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Título:
Euclidean distance between syntactically linked words
Autor:
Ferrer i Cancho, Ramon
Assuntos:
Artificial Intelligence
;
Average distance
;
Computational linguistics
;
Euclidean distance
;
Informàtica
;
Intel·ligència artificial
;
Linear Models
;
Lingüística computacional
;
Llenguatge natural
;
Natural Language Processing
;
Nonexcluding hypotheses
;
Pattern Recognition, Automated - methods
;
Semantics
;
Sentence length
;
Statistics as Topic
;
Syntactically linked words
;
Terminology as Topic
;
Vocabulary, Controlled
;
Àrees temàtiques de la UPC
É parte de:
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004-11, Vol.70 (5 Pt 2), p.056135-056135, Article 056135
Notas:
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição:
We study the Euclidean distance between syntactically linked words in sentences. The average distance is significantly small and is a very slowly growing function of sentence length. We consider two nonexcluding hypotheses: (a) the average distance is minimized and (b) the average distance is constrained. Support for (a) comes from the significantly small average distance real sentences achieve. The strength of the minimization hypothesis decreases with the length of the sentence. Support for (b) comes from the very slow growth of the average distance versus sentence length. Furthermore, (b) predicts, under ideal conditions, an exponential distribution of the distance between linked words, a trend that can be identified in real sentences.
Editor:
United States
Idioma:
Inglês
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