[aut, cre]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: | 0.9.4 |
| 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), ggwordcloud (≥ 0.5.0) |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-01-30 |
| 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 |
| CRAN checks: | akc results |
| Reference manual: | akc.pdf |
| Vignettes: |
akc_vignette tutorial_raw_text |
| Package source: | akc_0.9.4.tar.gz |
| Windows binaries: | r-devel: akc_0.9.4.zip, r-release: akc_0.9.4.zip, r-oldrel: akc_0.9.4.zip |
| macOS binaries: | r-release: akc_0.9.4.tgz, r-oldrel: akc_0.9.4.tgz |
| Old sources: | akc archive |
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