2026-01-11

Problem Overview

  • Modern typing applications assist users by predicting the next word.
  • These systems improve typing speed and user experience.
  • This project demonstrates a simple next-word prediction system using R.

Dataset and Motivation

  • The approach is inspired by the SwiftKey text dataset (blogs, news, Twitter).
  • For deployment efficiency, a small representative corpus was used.
  • This ensures fast loading and reliable performance on shinyapps.io.

Prediction Algorithm

  • Text is converted to lowercase and tokenized.
  • Bigrams (two-word sequences) are generated.
  • The last word entered by the user is matched against bigrams.
  • The most frequent following word is returned as the prediction.

Shiny Application

  • User enters a phrase containing multiple words.
  • On clicking Predict, the app computes the next word.
  • The output is a single predicted word.
  • The app is lightweight, responsive, and easy to use.

Conclusion

  • Demonstrates core Natural Language Processing concepts.
  • Efficient and suitable for real-time prediction.
  • Can be extended to larger datasets and higher-order n-grams.
  • Deployed using R Shiny and shared via RPubs.