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Next Word Predictor App Presentation
---
title: "Text Prediction App"
author: "Anila Mohanan"
output: ioslides_presentation
---
## Introduction
- Built as part of Coursera Data Science Capstone
- Predicts the next word in a user-entered phrase
- Uses blogs text dataset is used.
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## How the Algorithm Works
- Text cleaned and tokenized using `tidytext`
- Created **unigram**, **bigram**, and **trigram** frequency tables
- Uses **n-gram model with backoff**:
- If trigram not found → backoff to bigram → backoff to unigram
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## Prediction Model
- Efficient and memory-optimized using RDS storage
- Fast lookup using `dplyr` filtering and `slice_max`
- Handles unknown inputs with fallback strategy
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## Shiny App Demo
- Built using **Shiny** and hosted on **shinyapps.io**
- User enters a phrase → App predicts the next word
- Try it live here:
**https://x1tkzd-anila-mohanan.shinyapps.io/NextWordPredictor/**
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## Summary
- Accurate, fast predictions with minimal resources
- Real-time prediction from cleaned social and web text
- Could be extended into mobile keyboards or chat assistants
Milestone Report
This report presents a summary of the initial steps in developing a text prediction model using n-grams. It includes data loading, cleaning, tokenization, and a strategy for building a Shiny app.