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:	0.9.9
Depends:	R (≥ 4.0.0)
Imports:	igraph, dplyr, ggplot2, stringr, ggraph (≥ 1.0.2), tidygraph (≥ 1.1.2), ggforce, textstem, tibble, tidytext, rlang, magrittr, data.table (≥ 1.13.0), ggwordcloud (≥ 0.5.0), tidyfst
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2023-01-06
Author:	Tian-Yuan Huang [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
Citation:	akc citation info
CRAN checks:	akc results

Documentation:

Reference manual:	akc.pdf
Vignettes:	Benchmarking akc_vignette tutorial_raw_text

Downloads:

Package source:	akc_0.9.9.tar.gz
Windows binaries:	r-devel: akc_0.9.9.zip, r-release: akc_0.9.9.zip, r-oldrel: akc_0.9.9.zip
macOS binaries:	r-release (arm64): akc_0.9.9.tgz, r-oldrel (arm64): akc_0.9.9.tgz, r-release (x86_64): akc_0.9.9.tgz, r-oldrel (x86_64): akc_0.9.9.tgz
Old sources:	akc archive

Linking:

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