wordemb_FasttextEng_sample

<p>This is a data frame containing the 2,000 most frequently occurring
terms from Facebook's English-language fastText word embeddings model.</p>

data

A fast and computationally efficient algorithm designed to enable researchers to efficiently and quickly extract semantically-related keywords using a fitted embedding model. For more details about the methods applied, see Chester (2025). <doi:10.17605/OSF.IO/5B7RQ>.

Patrick Chester

keyclust

A Model for Semi-Supervised Keyword Extraction from Word
Embedding Models

wordemb_FasttextEng_sample function

<p>A 2000 row and 301 column data frame. The row represents the word embedding
term, while the numeric columns represent the word embedding dimension. The character
column gives the terms associated with each word vector.</p>

wordemb_FasttextEng_sample: Sample from the pre-trained English fastText model

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Examples