This is the final project for the Coursera Data Science Capstone. The goal of the capstone project is to create a predictive text model using a large text corpus of documents as training data.

For example, if a user types:

"I went to the …"

the app would suggest the three most likely words that would replace "…", i.e. gym, store or mall.

• The source codes of the app, the N-gram datasets and the algorithm available on GitHub repo at: https://github.com/Juanan4290/NextWordPredictor

• The shiny application developed for this course is available at: https://juanan4290.shinyapps.io/nextwordpredictor/

Head of "fourgrams" and "trigrams" data frames loaded by Next Word Predictor App:

##                    Word Freq                 Prob
## 1 thanks for the follow 2027 0.000207001660098168
## 2     thanks for the rt 1115 0.000113866231381084
## 3      cant wait to see 1058 0.000108045267086266
## 4     thank you for the 1021 0.000104266746403665
## 5        is going to be  768 7.84298347091233e-05
## 6     thank you so much  726 7.41407031234682e-05

##                 Word Freq                 Prob
## 1     thanks for the 7830 0.000799616674182859
## 2 looking forward to 2863 0.000292375803088828
## 3       cant wait to 2835 0.000289516382031725
## 4      thank you for 2812 0.000287167571877676
## 5         i love you 2770  0.00028287844029202
## 6     for the follow 2545 0.000259900949654582

Main steps to achieve next word predictions:

1. Loading 4 data frames contained n-grams combinations with 4-words, 3-words, 2-words, and 1-word previously generated.
2. Reading user input (a word or sentence).
3. Cleaning user input (lowering, tokenization of input words: the last four)
4. Call to prediction model function:
   • Search in the fourgram data frame. If found, shows top 5 most probable matches. Otherwise:
   • Search in the trigram data frame, by the same way above. Otherwise:
     
   • Search in bigram data frame, by the same way above.
   • Else, at last, if none matching, displays the most frequent words in the unigram data frame.

This is how the Next Word Predictor Application looks like:

In the left side you can insert a word or sentence and once you click on Predict button or press Enter the app will display some words suggested and other information like which N-gram next word was predict with, time invested to procces the algorithm or cleaned text for prediction.