In the fields of computational linguistics and probability, an n-gram is a contiguous sequence of n items from a given sequence of text or speech. The n-grams typically are collected from a text or speech corpus. An n-gram of size 1 is referred to as a “unigram”; size 2 is a “bigram” (or, less commonly, a “digram”); size 3 is a “trigram”. Larger sizes are sometimes referred to by the value of n in modern language, e.g., “four-gram”, “five-gram”, and so on.

(Source: https://en.wikipedia.org/wiki/N-gram)

https://moooor.shinyapps.io/word_prediction_app/

Shiny App Screenshot

This app uses text samples of three large text files to create a corpus as source text for the n-gram algorithm which is saved as an .RData file.

N-grams were developed at three levels (uni-, bi-, tri-), with J-M smoothing and part-of-speech tagging.

That file is then tokenized into bigrams, trigrams, and fourgrams, sorted by n-gram frequency, and stored in three .RData files for bigrams, trigrams, and fourgrams that can be used by the application to look up word sequences.

• Punctuation is currently completely ignored
• Languages other than English are completely ignored
• Spelling mistakes are not handled
  
  
  
  Thank you!