akc: Automatic Knowledge Classification

A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.

Version: 0.9.1
Depends: R (≥ 3.0.0)
Imports: igraph, dplyr, ggplot2, stringr, ggraph (≥ 1.0.2), tidygraph (≥ 1.1.2), ggforce, textstem, tibble, tidytext, widyr, rlang, magrittr, data.table (≥ 1.12.6)
Suggests: knitr, rmarkdown
Published: 2020-01-09
Author: Tian-Yuan Huang ORCID iD [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan at qq.com>
License: MIT + file LICENSE
URL: https://github.com/hope-data-science/akc
NeedsCompilation: no
Materials: README
CRAN checks: akc results

Downloads:

Reference manual: akc.pdf
Vignettes: akc_vignette
Package source: akc_0.9.1.tar.gz
Windows binaries: r-devel: akc_0.9.1.zip, r-devel-gcc8: akc_0.9.1.zip, r-release: akc_0.9.1.zip, r-oldrel: akc_0.9.1.zip
OS X binaries: r-release: akc_0.9.1.tgz, r-oldrel: akc_0.9.1.tgz
Old sources: akc archive

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