oncrawlR: Machine Learning for S.E.O

Measures different aspects of page content, structure and performance for SEO (Search Engine Optimization). Aspects covered include HTML tags used in SEO, duplicate and near-duplicate content, structured data, on-site linking structure and popularity transfer, and many other amazing things. This package can be used to generate a real, full SEO audit report, which serves to detect errors or inefficiencies on a page that can be corrected in order to optimise its performance on search engines.

Version: 0.2.0
Depends: R (≥ 3.4.0)
Imports: RCurl (≥ 1.8), jsonlite (≥ 1.6), dplyr (≥ 0.7), xgboost (≥ 0.8), pROC (≥ 1.1), ggplot2 (≥ 3.1), caret (≥ 6.0), DALEX (≥ 0.3), rlist (≥ 0.4.6), readr (≥ 1.3), rlang (≥ 0.3), formattable (≥ 0.2), sparkline (≥ 0.2), webshot (≥ 0.5), e1071 (≥ 1.7), pdp (≥ 0.7), fs (≥ 1.3), scales (≥ 1.0.0), tidyr (≥ 0.8.2), htmltools (≥ 0.3.5), rjson (≥ 0.2.20)
Suggests: devtools (≥ 1.12.0), testthat
Published: 2020-01-31
Author: Vincent Terrasi [aut, cre], OnCrawl [cph, fnd]
Maintainer: Vincent Terrasi <vincent at oncrawl.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: oncrawlR results

Documentation:

Reference manual: oncrawlR.pdf

Downloads:

Package source: oncrawlR_0.2.0.tar.gz
Windows binaries: r-devel: oncrawlR_0.2.0.zip, r-release: oncrawlR_0.2.0.zip, r-oldrel: oncrawlR_0.2.0.zip
macOS binaries: r-release (arm64): oncrawlR_0.2.0.tgz, r-release (x86_64): oncrawlR_0.2.0.tgz, r-oldrel: oncrawlR_0.2.0.tgz
Old sources: oncrawlR archive

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