get_local_vocab

Local vocab consists of the intersect between the set of pretrained embeddings
and the collection of texts.

A fast, flexible and transparent framework to estimate context-specific word and short document embeddings using the 'a la carte'
embeddings approach developed by Khodak et al. (2018) <arXiv:1805.05388> and evaluate hypotheses about covariate effects on embeddings using
the regression framework developed by Rodriguez et al. (2021)<https://github.com/prodriguezsosa/EmbeddingRegression>.

Pedro L. Rodriguez

conText

'a la Carte' on Text (ConText) Embedding Regression

Arthur Spirling

Brandon Stewart

Christopher Barrie

get_local_vocab function

<dl><dt>context</dt>
<dd>(character) vector of contexts (usually <code>context</code> in <code>get_context()</code> output)</dd>
<dt>pre_trained</dt>
<dd>(numeric) a F x D matrix corresponding to pretrained embeddings.
F = number of features and D = embedding dimensions.
rownames(pre_trained) = set of features for which there is a pre-trained embedding.</dd></dl>

Arguments

Identify words common to a collection of texts and a set of pretrained embeddings. — get_local_vocab

<dl>

<dt>context</dt>
<dd>(character) vector of contexts (usually <code>context</code> in <code>get_context()</code> output)</dd>


<dt>pre_trained</dt>
<dd>(numeric) a F x D matrix corresponding to pretrained embeddings.
F = number of features and D = embedding dimensions.
rownames(pre_trained) = set of features for which there is a pre-trained embedding.</dd>

</dl>

get_local_vocab: Identify words common to a collection of texts and a set of pretrained embeddings.

Description

Usage

Value

Arguments

Examples