<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Claim

Euclidean distance between syntactically linked words

Name: Euclidean distance between syntactically linked words
Creator: Ramon Ferrer i Cancho
Keywords: Statistics as Topic, Computational linguistics, Euclidean distance matrix, Pattern Recognition, Automated, Combinatorics, Artificial Intelligence, Terminology as Topic, Nonexcluding hypotheses, Jaro–Winkler distance, Distance from a point to a line

descriptionPublicationkeyboard_double_arrow_right Article 26 Apr 2004 Spain American Physical Society (APS)Physical Review E, volume 70 (issn: 1539-3755, eissn: 1550-2376,

Authors: Ramon Ferrer i Cancho;

doi: 10.1103/physreve.70.056135

pmid: 15600720

handle: 2117/175762

Euclidean distance between syntactically linked words

- Summary
- Subjects
- Metrics

Abstract

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. Peer Reviewed

Country

Spain

Related Organizations

Universitat Politènica de Catalunya
Spain
Universitat Pompeu Fabra
Spain

Subjects by Vocabulary

Microsoft Academic Graph classification: Euclidean distance matrix Combinatorics Jaro–Winkler distance Distance from a point to a line Mathematics Discrete mathematics Mahalanobis distance Minkowski distance Euclidean distance Distance matrix Total variation distance of probability measures

arXiv: Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)

Keywords

Statistics as Topic, Computational linguistics, Pattern Recognition, Automated, Artificial Intelligence, Terminology as Topic, Nonexcluding hypotheses, Natural Language Processing, Average distance, Syntactically linked words, Semantics, Vocabulary, Controlled, Sentence length, Linear Models, Lingüística computacional, Euclidean distance, :Informàtica::Intel·ligència artificial::Llenguatge natural [Àrees temàtiques de la UPC]

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	91
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%

Usage byUsageCounts

visibility	views	83
download	downloads	447

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	91
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%