txt_count_words

The C++ doc2vec functionalities in this package assume words are either separated 
by a space or tab symbol and that each document contains less than 1000 words. 
This function calculates how many words there are in each element of a character vector by counting
the number of occurrences of the space or tab symbol.

Learn vector representations of sentences, paragraphs or documents by using the 'Paragraph Vector' algorithms,
namely the distributed bag of words ('PV-DBOW') and the distributed memory ('PV-DM') model.
The techniques in the package are detailed in the paper "Distributed Representations of Sentences and Documents" by Mikolov et al. (2014), available at <doi:10.48550/arXiv.1405.4053>.
The package also provides an implementation to cluster documents based on these embedding using a technique called top2vec.
Top2vec finds clusters in text documents by combining techniques to embed documents and words and density-based clustering.
It does this by embedding documents in the semantic space as defined by the 'doc2vec' algorithm. Next it maps
these document embeddings to a lower-dimensional space using the 'Uniform Manifold Approximation and Projection' (UMAP) clustering algorithm
and finds dense areas in that space using a 'Hierarchical Density-Based Clustering' technique (HDBSCAN). These dense
areas are the topic clusters which can be represented by the corresponding topic vector which is an aggregate of the
document embeddings of the documents which are part of that topic cluster. In the same semantic space similar words can
be found which are representative of the topic.
More details can be found in the paper 'Top2Vec: Distributed Representations of Topics' by D. Angelov available at <doi:10.48550/arXiv.2008.09470>.

Jan Wijffels

doc2vec

Distributed Representations of Sentences, Documents and Topics

BNOSAC 

hiyijian 

txt_count_words function

<dl><dt>x</dt>
<dd>a character vector with text</dd>
<dt>pattern</dt>
<dd>a text pattern to count which might be contained in <code>x</code>. Defaults to either space or tab.</dd>
<dt>...</dt>
<dd>other arguments, passed on to <code><a href="/link/gregexpr?package=doc2vec&version=0.2.2" data-mini-rdoc="doc2vec::gregexpr">gregexpr</a></code></dd></dl>

Arguments

The C++ doc2vec functionalities in this package assume words are either separated 
by a space or tab symbol and that each document contains less than 1000 words. 
This function calculates how many words there are in each element of a character vector by counting
the number of occurrences of the space or tab symbol.

Count the number of spaces occurring in text — txt_count_words

<dl>

<dt>x</dt>
<dd>a character vector with text</dd>


<dt>pattern</dt>
<dd>a text pattern to count which might be contained in <code>x</code>. Defaults to either space or tab.</dd>


<dt>...</dt>
<dd>other arguments, passed on to <code><a href='https://rdrr.io/r/base/grep.html'>gregexpr</a></code></dd>

</dl>

txt_count_words: Count the number of spaces occurring in text

Description

Usage

Value

Arguments

Examples