• Title: Word Prediction App
• Objective: To present an innovative app for predicting the next word based on user input.
• Target Audience: Businesses and researchers looking for advanced text prediction solutions.

• Algorithm:
  • Utilizes a dictionary of common words, phrases, numbers, and salutations.
  • Employs an n-gram model to predict the next word.
  • Provides suggestions based on the input text.
• Benefits:
  • Enhances user experience with fast and accurate predictions.
  • Easy integration with various applications and platforms.

• Features:
  • User-friendly interface with a text input box.
  • Predicts the next word when the user clicks “Predict Next Word”.
  • Displays predictions based on an extensive dictionary.
• Demo:
  • Live demo of the app.
  • Examples of word predictions in action.

• Technology:
  • Built with R and Shiny.
  • Utilizes the quanteda package for text processing and prediction.
• Challenges:
  • Handling large dictionaries and ensuring quick responses.
  • Continuous updates to improve prediction accuracy.

Here is an example plot demonstrating how the document-feature matrix is visualized: