Biplot Graphical Interface for LDA Models
c(person(given = "Luis",
family = "Pilacuan-Bonete",
role = c("cre","aut"),
email = "luis.pilacuanb@ug.edu.ec",
comment = c(ORCID = "0000-0002-6625-0905")),
person(given = "Purificacion",
family = "Galindo-Villardón",
role = c("aut"),
email = "pgalindo@usal.es",
comment = c(ORCID = "0000-0001-6977-7545")),
person(given = "Javier",
family = "De La Hoz Maestre",
role = c("aut"),
email = "jdelahoz@unimagdalena.edu.co",
comment = c(ORCID = "0000-0001-7779-0803")),
person(given = "Francisco Javier",
family = "Delgado-Álvarez",
role = c("aut"),
email = "j.delgado@usal.es",
comment = c(ORCID = "0000-0002-2626-2709")))
Contains the development of a tool that provides a web-based graphical
user interface (GUI) to perform Biplots representations from a scraping of
news from digital newspapers under the Bayesian approach of Latent Dirichlet
Assignment (LDA) and machine learning algorithms. Contains LDA methods
described by Blei , David M., Andrew Y. Ng and Michael I. Jordan (2003)
<https://jmlr.org/papers/volume3/blei03a/blei03a.pdf>,
and Biplot methods described by Gabriel K.R(1971) <doi:10.1093/biomet/58.3.453>
and Galindo-Villardon P(1986) <https://diarium.usal.es/pgalindo/files/2012/07/Questiio.pdf>.
shiny, shinyBS, shinydashboard, shinyWidgets, shinyalert,
shinybusy, shinyjs, shinycssloaders, dplyr, ggplot2, rvest, DT,
highcharter, tidyr, SnowballC, ldatuning, topicmodels,
textmineR, chinese.misc, stringr, htmlwidgets, ggrepel,
textplot, glasso, qgraph, Matrix, utils, factoextra, quanteda
Luis Pilacuan-Bonete [cre, aut]
(<https://orcid.org/0000-0002-6625-0905>),
Purificacion Galindo-Villardón [aut]
(<https://orcid.org/0000-0001-6977-7545>),
Javier De La Hoz Maestre [aut]
(<https://orcid.org/0000-0001-7779-0803>),
Francisco Javier Delgado-Álvarez [aut]
(<https://orcid.org/0000-0002-2626-2709>)

User-Friendly Interface for Review of Scientific Literature
c(person(given = "Javier",
family = "De La Hoz Maestre",
role = c("cre", "aut"),
email = "jdelahozmaestre@gmail.com",
comment = c(ORCID = "0000-0001-7779-0803")),
person(given = "María José",
family = "Fernández Gómez",
role = "aut",
email = "mjfg@usal.es",
comment = c(ORCID = "0000-0002-5530-6416")),
person(given = "Susana",
family = "Mendez",
role = "aut",
email = "Susana.mendes@ipleiria.pt",
comment = c(ORCID = "0000-0001-9681-3169")))
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>.
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
knitr, RColorBrewer, rmarkdown, Rmpfr, scales, magrittr