Graphical user interface providing an integrated text mining
solution
Snowball, RWeka, Rstem, ROpenOffice, RODBC,
tm.plugin.factiva, twitteR

Rcmdr (>= 2.1-1), tcltk, tcltk2, utils, ca, R2HTML (>= 2.3.0),
RColorBrewer, latticeExtra, stringi
methods, tm (>= 0.6), NLP, slam, zoo, lattice
SnowballC, ROpenOffice, RODBC, tm.plugin.factiva (>= 1.4),
tm.plugin.lexisnexis (>= 1.1), tm.plugin.europresse (>= 1.1),
tm.plugin.alceste (>= 1.1), twitteR
An R Commander plug-in providing an integrated solution to perform
a series of text mining tasks such as importing and cleaning a corpus, and
analyses like terms and documents counts, vocabulary tables, terms
co-occurrences and documents similarity measures, time series analysis,
correspondence analysis and hierarchical clustering. Corpora can be imported
from spreadsheet-like files, directories of raw text files, Twitter queries,
as well as from Dow Jones Factiva, LexisNexis, Europresse and Alceste files.

An 'R Commander' plug-in providing an integrated solution to perform
a series of text mining tasks such as importing and cleaning a corpus, and
analyses like terms and documents counts, vocabulary tables, terms
co-occurrences and documents similarity measures, time series analysis,
correspondence analysis and hierarchical clustering. Corpora can be imported
from spreadsheet-like files, directories of raw text files, 'Twitter' queries,
as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files.

methods, Rcmdr (>= 2.0-0), tcltk, tcltk2, utils, ca, R2HTML,
RColorBrewer, latticeExtra, stringi

Functions for co-clustering with C code illustrating two diagonal approaches,
(Ailem & Role & Nadif, 2016, <doi:10.1016/j.knosys.2016.07.002>),
(Laclau & Nadif, 2016, <doi:10.1016/j.neucom.2016.02.003>).
A relevant initialization and a suitable setting of the parameters are required.
For a dimensionality reduction via random projection, a function is included.

Several co-clustering algorithms are implemented for sparse binary and contingency matrices.
They aim at a simultaneous clustering of the rows and the columns via an objective function.