Understanding the spatial dimension of natural language by measuring the spatial semantic similarity of words through a scalable geospatial context window

Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial semantics of implied spatial information are rarely pre...

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Detalles Bibliográficos
Autores principales: Wang, Bozhi, Fei, Teng, Kang, Yuhao, Li, Meng, Du, Qingyun, Han, Meng, Dong, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7377466/
https://www.ncbi.nlm.nih.gov/pubmed/32702022
http://dx.doi.org/10.1371/journal.pone.0236347

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7377466/
https://www.ncbi.nlm.nih.gov/pubmed/32702022
http://dx.doi.org/10.1371/journal.pone.0236347

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