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Linguistic Typology

Ed. by Plank, Frans

3 Issues per year


IMPACT FACTOR 2016: 0.304

CiteScore 2016: 0.53

SCImago Journal Rank (SJR) 2015: 0.663
Source Normalized Impact per Paper (SNIP) 2015: 1.377

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ISSN
1613-415X
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Volume 17, Issue 1 (Jun 2013)

Issues

Inferring semantic maps

Terry Regier
  • University of California Berkeley
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/ Naveen Khetarpal
  • The University of Chicago
  • Email:
/ Asifa Majid
  • Max Planck Institute for Psycholinguistics
  • Email:
Published Online: 2013-07-06 | DOI: https://doi.org/10.1515/lity-2013-0003

Abstract

Semantic maps are a means of representing universal structure underlying semantic variation. However, no algorithm has existed for inferring a graph-based semantic map from cross-language data. Here, we note that this open problem is formally identical to the known problem of inferring a social network from disease outbreaks. From this identity it follows that semantic map inference is computationally intractable, but that an efficient approximation algorithm for it exists. We demonstrate that this algorithm produces sensible semantic maps from two existing bodies of data. We conclude that universal semantic graph structure can be automatically approximated from cross-language semantic data.

This article offers supplementary material which is provided at the end of the article.

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Published Online: 2013-07-06

Published in Print: 2013-06-15



Citation Information: Linguistic Typology, ISSN (Online) 1613-415X, ISSN (Print) 1430-0532, DOI: https://doi.org/10.1515/lity-2013-0003. Export Citation

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