foreign: Read Document-Term Matrices

In tm: Text Mining Package

Read Document-Term Matrices

Description

Read document-term matrices stored in special file formats.

Usage

read_dtm_Blei_et_al(file, vocab = NULL)
read_dtm_MC(file, scalingtype = NULL)

Arguments

file	a character string with the name of the file to read.
vocab	a character string with the name of a vocabulary file (giving the terms, one per line), or NULL.
scalingtype	a character string specifying the type of scaling to be used, or NULL (default), in which case the scaling will be inferred from the names of the files with non-zero entries found (see Details).

Details

read_dtm_Blei_et_al reads the (List of Lists type sparse matrix) format employed by the Latent Dirichlet Allocation and Correlated Topic Model C codes by Blei et al (http://www.cs.columbia.edu/~blei/).

MC is a toolkit for creating vector models from text documents (see https://www.cs.utexas.edu/~dml/software/mc/). It employs a variant of Compressed Column Storage (CCS) sparse matrix format, writing data into several files with suitable names: e.g., a file with ‘_dim’ appended to the base file name stores the matrix dimensions. The non-zero entries are stored in a file the name of which indicates the scaling type used: e.g., ‘_tfx_nz’ indicates scaling by term frequency (‘⁠t⁠’), inverse document frequency (‘⁠f⁠’) and no normalization (‘⁠x⁠’). See ‘README’ in the MC sources for more information.

read_dtm_MC reads such sparse matrix information with argument file giving the path with the base file name.

Value

A document-term matrix.

See Also

read_stm_MC in package slam.

tm documentation built on Sept. 11, 2024, 6:47 p.m.