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Data · dataset · 2017

Word embeddings obtained from decow14ax - 300 dimensional

Listed in Research Data Repository FDAT

Word vectors trained using GloVe for the most frequent 1000000 tokens in the decow14ax corpus.

Description

See associated paper (Dima, 2015) for description of the training parameters. word embeddings - distributional representations - word vectors GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space.

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Where it is published

Catalogue records · 1

Topics

Stated by source
linguistics
From keywords
Humanities · Linguistics
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
Research Data Repository FDATrh8q5-56q812 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0
concepts[field].anzsrc:group:4704mapping · fdat uni tuebingen devocabulary-mapper@1.0.0keywords['linguistics']
concepts[field].local:field:humanitiesmapping · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0
concepts[topic].invenio_subject:fdat_uni_tuebingen_de:linguisticssource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0
descriptionsource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0/metadata/description
publication_datesource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0
titlesource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0/metadata/title
updated_datesource · fdat uni tuebingen deconnector:fdat_uni_tuebingen_de@1.0.0