2025-02-04

The Project

This project uses Natural Language Processing (NLP).

The critical task is to take a user’s input phrase and output a predicted next word(s).

This presentation features the NLP Next Word Predict application including an instruction tab to

the application user interface and details about the text prediction algorithm.

Project deliverables:

  • NLP (Next Word) Prediction Model, is basis for this application.
  • NLP Prediction App hosted at shinyapps.io
  • This presentation hosted at R pubs

NLP Next Word Prediction Model

  1. Input: raw text files for model training
  2. Clean training data; separate into 2 words, 3 words, and 4 words n-grams.
  3. Sort n-grams by frequency, and save them as data repos
  4. N-grams function: uses a “back-off” type prediction model
  • user supplies an input phrase
  • model uses the last 3, 2, or 1 word to predict the best 4th, 3rd, or 2nd match in the repos
  1. Output: next word prediction

Benefits: easy to read code; uses “pipes”; fast processing of training data; able to sample up to 25% of original corpus; relatively small output repos

NLP Prediction Application for Next Word

The next word prediction application provides an easy-to-use user interface to the next word prediction model.

Top Features:

  1. Text box for user input
  2. Predicted next word outputs dynamically below user input
  3. Tabs with plots of most frequent n-grams in the data-set
  4. Side panel with user instructions

Overall Benefits:

  1. Fast response
  2. Method allows for large training sets leading to improve next-word predictions and user experience

Demo Application:

NLP Shiny App Link

Documentation and Source Code