• This application is the capstone project for the Coursera Data Science specialization in cooperation with SwiftKey.
• The main goal of this capstone project is to build a shiny application that is able to predict the next word as accurately as possible.
• The text data is used to form a frequency dictionary and then to predict the next words. This data comes from a corpus called HC Corpora.

• After creating a data sample from the HC Corpora data, this sample was cleaned by conversion to lowercase, removing punctuation, links, white space, numbers and all kinds of special characters.

• This data sample was then tokenized into n-grams.

• Those aggregated bi-,tri- and quadgram term frequency matrices have been transferred into frequency dictionaries.

• Lastly, the resulting data frames are used to predict the next word in connection with the text input by a user of the described application and the frequencies of the underlying n-grams table.

The usage is pretty straightforward.

1. Enter text
2. The field with the predicted next word refreshes instantaneously
3. Also the whole text input gets displayed.

• The next word prediction app is hosted on shinyapps.io

• GitHub repository