LDAShiny: User-Friendly Interface for Review of Scientific Literature

Contains the development of a tool that provides a web-based graphical user interface (GUI) to perform a review of the scientific literature under the Bayesian approach of Latent Dirichlet Allocation (LDA)and machine learning algorithms. The application methodology is framed by the well known procedures in topic modelling on how to clean and process data. Contains methods described by Blei, David M., Andrew Y. Ng, and Michael I. Jordan (2003) <https://jmlr.org/papers/volume3/blei03a/blei03a.pdf> Allocation"; Thomas L. Griffiths and Mark Steyvers (2004) <doi:10.1073/pnas.0307752101> ; Xiong Hui, et al (2019) <doi:10.1016/j.cie.2019.06.010>.

Version: 0.9.2
Imports: beepr, broom, chinese.misc, dplyr, DT (≥ 0.15), highcharter, htmlwidgets, ldatuning, parallel, plotly, purrr, quanteda, shiny, shinyalert, shinyBS, shinycssloaders, shinydashboard, shinydashboardPlus, shinyjs, shinyWidgets, SnowballC, stringr, textmineR, tidyr, tidytext, tm, topicmodels
Suggests: knitr, RColorBrewer, rmarkdown, Rmpfr, scales, magrittr
Published: 2021-02-05
Author: Javier De La Hoz Maestre ORCID iD [cre, aut], María José Fernández Gómez ORCID iD [aut], Susana Mendez ORCID iD [aut]
Maintainer: Javier De La Hoz Maestre <jdelahozmaestre at gmail.com>
BugReports: https://github.com/JavierDeLaHoz/LDAShiny/issues
License: GPL-3
NeedsCompilation: no
CRAN checks: LDAShiny results

Downloads:

Reference manual: LDAShiny.pdf
Vignettes: A brief introduction to LDAShiny
Una breve introducción a LDAShiny
Package source: LDAShiny_0.9.2.tar.gz
Windows binaries: r-devel: LDAShiny_0.9.2.zip, r-release: LDAShiny_0.9.2.zip, r-oldrel: LDAShiny_0.9.2.zip
macOS binaries: r-release: LDAShiny_0.9.2.tgz, r-oldrel: LDAShiny_0.9.2.tgz

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