Package: LDAShiny 0.9.3

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>.

Authors:Javier De La Hoz Maestre [cre, aut], María José Fernández Gómez [aut], Susana Mendez [aut]

LDAShiny_0.9.3.tar.gz
LDAShiny_0.9.3.zip(r-4.5)LDAShiny_0.9.3.zip(r-4.4)LDAShiny_0.9.3.zip(r-4.3)
LDAShiny_0.9.3.tgz(r-4.4-any)LDAShiny_0.9.3.tgz(r-4.3-any)
LDAShiny_0.9.3.tar.gz(r-4.5-noble)LDAShiny_0.9.3.tar.gz(r-4.4-noble)
LDAShiny_0.9.3.tgz(r-4.4-emscripten)LDAShiny_0.9.3.tgz(r-4.3-emscripten)
LDAShiny.pdf |LDAShiny.html
LDAShiny/json (API)

# Install 'LDAShiny' in R:
install.packages('LDAShiny', repos = c('https://javierdelahoz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/javierdelahoz/ldashiny/issues

Datasets:
  • crude - 20 Exemplary News Articles from the Reuters-21578 Data Set of Topic crude

On CRAN:

2 exports 3 stars 1.02 score 137 dependencies 3 scripts 1.2k downloads

Last updated 3 years agofrom:204cfe108f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-winNOTEAug 28 2024
R-4.5-linuxNOTEAug 28 2024
R-4.4-winNOTEAug 28 2024
R-4.4-macNOTEAug 28 2024
R-4.3-winNOTEAug 28 2024
R-4.3-macNOTEAug 28 2024

Exports:removeSparseTermsrunLDAShiny

Dependencies:anytimeaskpassassertthataudiobackportsbase64encbeeprBHbroombslibcachemchinese.miscclicolorspacecommonmarkcpp11crayoncrosstalkcurldata.tabledigestdplyrDTevaluatefansifarverfastmapfastmatchfloatfontawesomefsgenericsggplot2gluegmpgtablegtoolshighcharterhighrhtmltoolshtmlwidgetshttpuvhttrigraphisobandISOcodesjaneaustenrjiebaRjiebaRDjquerylibjsonliteknitrlabelinglaterlatticelazyevalldatuninglgrlifecyclelubridatemagrittrMASSMatrixMatrixExtramemoisemgcvmimemlapimodeltoolsmunsellnlmeNLPopensslpillarpkgconfigplotlyplyrpromisespurrrquantedaquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressreshape2RhpcBLASctlrjsonrlangrlistrmarkdownRmpfrrsparseRSpectrasassscalesshinyshinyalertshinyBSshinycssloadersshinydashboardshinyjsshinyWidgetsslamSnowballCsourcetoolsstopwordsstringistringrsystext2vectextmineRtibbletidyrtidyselecttidytexttimechangetinytextmtokenizerstopicmodelsTTRutf8uuidvctrsviridisLitewithrxfunXMLxml2xtablextsyamlzoo

A brief introduction to LDAShiny

Rendered fromA_brief_introduction_to_LDAShiny.Rmdusingknitr::rmarkdownon Aug 28 2024.

Last update: 2021-01-30
Started: 2021-01-22

Una breve introducción a LDAShiny

Rendered fromUna_breve_introducci-n_a_LDAShiny.Rmdusingknitr::rmarkdownon Aug 28 2024.

Last update: 2021-01-30
Started: 2021-01-22