Planned maintenance
A system upgrade is planned for 10/12-2024, at 12:00-13:00. During this time DiVA will be unavailable.
EnglishSvenskaNorsk
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Grammatical gender in Swedish is predictable using recurrent neural networks
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0001-7856-113X
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0002-9567-2218
2019 (English)In: PROCEEDINGS OF THE 15THSWECOG CONFERENCE, 2019, p. 43-45Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
2019. p. 43-45
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-51867OAI: oai:DiVA.org:ri-51867DiVA, id: diva2:1518359
Conference
15TH SWECOG CONFERENCE. Umeå, Sweden. 7-8 November, 2019.
Available from: 2021-01-15 Created: 2021-01-15 Last updated: 2024-05-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Fulltext

Authority records

Zec, Edvin ListoMogren, Olof

Search in DiVA

By author/editor
Zec, Edvin ListoMogren, Olof
By organisation
Data Science
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 209 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.44.0
|
WCAG