Have you ever wondered how nice it would be if you could have an app

• where you entered a phrase and the next word automatically gets suggested?
• where you just enter one word and the next word gets automatically predicted?

If your answer to any of these questions is yes - then this app is for you!

• DATA which includes (3) text files containing randomized information from
• blogs with 899288 lines of text containing 37334131 words!
• news with 77259 lines of text containing 2643969 words!
• twitter feeds with 2360148 lines of text containing 30373543 words!

Preprocessing, which involves

• using tidytext to clean data,i.e.remove stop words, extra spaces, random letters, etc.

Breaking down each file into

• bigrams (groups of two words occuring successively)
• trigrams (groups of three words occuring successively)

• By first only filtering bigrams and trigrams that exceed a certain frequency of occurance
• By sorting bigrams based on the first word
• By sorting trigrams based on the first word and then the second word
• Creating a new probability column which assigns a value for the likelihood for a word to occur, given the first word for bigrams
• Creating a new probability column which assigns a value for the likelihood for a word to occur, given the first and second word for trigrams
• In both of the above cases, the word with the highest probability would then be predicted

• This app demostrates the free and simple version v1 of the word prediction app

We plan on adding new features for v2 that include:

• Showing values for actual number of occurances for the predicted word
• Increasing the database by including words from other sources, news articles, journals, etc.
• Sentiment analysis

The author would like to credit: https://web.stanford.edu/~jurafsky/slp3/3.pdf for ideas on how to implement the ngram models discussed in the presentation