The purpose of the project is to create text-prediction application with R Shiny package that predicts words using a natural language processing model i.e. creating an application based on a predictive model for text. The goal of the project is to build a predictive text model combined with a shiny app UI that will predict the next word as the user types a sentence similar to the way most smart phone keyboards are implemented today using the technology of Swiftkey.

[Shiny App] - [https://madanweb30.shinyapps.io/Data-Science-Capstone-Final-Project/]

[Github Repo] - [https://github.com/madanweb30/Data-Science-Capstone-Final-Project]

Before building the word prediction algorithm, data are first processed and cleaned as steps below:

• A subset of the original data was sampled from the three sources (blogs,twitter and news) which is then merged into one.
• Next, data cleaning is done by conversion to lowercase, strip white space, and removing punctuation and numbers.
• The corresponding n-grams are then created (Quadgram,Trigram and Bigram).
• Next, the term-count tables are extracted from the N-Grams and sorted according to the frequency in descending order.
• Lastly, the n-gram objects are saved as R-Compressed files (.RData files)
• The prediction model uses the principles of tidy data applied to text mining in R

Explanation of the next word prediction flow is as below:

• Compressed data sets containing descending frequency sorted n-grams are first loaded.
• User input words are cleaned in the similar way as before prior to prediction of the next word.
• For prediction of the next word, Quadgram is first used (first three words of Quadgram are the last three words of the user provided sentence).
• If no Quadgram is found, back off to Trigram (first two words of Trigram are the last two words of the sentence).
• If no Trigram is found, back off to Bigram (first word of Bigram is the last word of the sentence)
• If no Bigram is found, back off to the most common word with highest frequency ‘the’ is returned.

A Shiny application was developed based on the next word prediction model described previously as shown below.

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