Precognition of Content by Interpreting Human Language Into Computer Automated Data Processing

Abstract

Text has become a major part of our life. We use text as way to communicate and express ourselves in this sophisticated world. Since we are predicting the next probable "word" we will be using text as input data for our algorithm. Predictive typing is basically predicting the most probable word following the given set of words or a particular word. In this contemporary world where mobile devices and computers dominate communication, like emails, social media and even blogs and newsletters, we require a method for speeding up the responding process to keep ourselves with the fast-paced world. Predictive typing is a widely used procedure for faster and eloquent communication but the robustness and scalability along with the speed is always a concern. The main aim of our algorithm is to develop a next word predictor that helps to significantly reduce the number of key-strokes by the user along with accuracy. This predictive typing algorithm’s core is based on the N-grams model.