voltek62

library(httr)
library(jsonlite)

# https://dataseolabs.com
# Doc : https://www.similarweb.com/corp/developer/
# Create your key here : https://pro.similarweb.com/#/account/api-management
# You can have freely 3 Months of Web Traffic Data 

# conf
myList <- c("cuisineaz.com","marmiton.org","odelices.com","allrecipes.fr")

voltek62

library(httr)
library(urltools)
library(dplyr)

# https://dataseolabs.com
# Doc : https://developer-support.majestic.com/api/
# Create your key here : https://developer-support.majestic.com/security/

apiUrl <- "https://api.majestic.com/api/json?app_api_key="
apiKey <- "YOURKEY"

voltek62

library(dplyr)

# https://dataseolabs.com
# Doc : https://fr.semrush.com/api-documentation/
# Get your key here : https://fr.semrush.com/billing-admin/profile/subscription/api-units

# conf
keyAPI <- "YOURKEY"
domain <- "cnn.com"
country <- "fr"

voltek62

library(googleAnalyticsR)

# https://dataseolabs.com

## authentication with both GA and SC
options(googleAuthR.scopes.selected = 
          c("https://www.googleapis.com/auth/analytics",
            "https://www.googleapis.com/auth/analytics.readonly"))

voltek62

library(searchConsoleR)

# https://dataseolabs.com

## authentication with both GA and SC
options(googleAuthR.scopes.selected = 
          c("https://www.googleapis.com/auth/webmasters"))

googleAuthR::gar_auth()

voltek62

# install.packages("ngram")
# install.packages("tm")

library(ngram)
library(tm)

# read txt file
url <- "https://raw.githubusercontent.com/voltek62/RsparkleR-examples/master/examples/advs.txt"
txt <- readLines(url)
data.sentence <- concatenate(txt)

voltek62

#autoinstall packages
packages <- c("igraph", "dplyr", "ggplot2", "magrittr")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())))  
}

# Enjoy learning ? https://dataseolabs.com

library(igraph)
library(dplyr)

voltek62

voltek62

Machine Learning Repository for SEO

SEO is a field that is rich with data, yet many young SEOs may not be equipped to learn tools that will prepare them for the future. We want to support our community by using our expertise to provide access to more advanced tools that will allow SEOs of all levels to play with the technologies that will shape the future of our work.

Objectives

• Provide a repositiory that makes it possible to learn about ML specifically targeted to those interested in SEO
• Provide a repository that allows a novice user to run a simple model on something meaningful for SEO.
• Provide a repository that allows advanced users to save time on data getting, cleaning, preprocessing, and model selection.
• Allow users to showcase work and models developed.
• Have users get involved with the future development of the repo.

voltek62

#autoinstall packages
packages <- c("rJava", "boilerpipeR", "httr")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())))  
}

# Enjoy learning ? https://dataseolabs.com

# configure your jre
Sys.setenv(JAVA_HOME='C:\\Program Files\\Java\\jre1.8.0_181') # for 64-bit version