This project implements an intelligent system that can learn to choose the correct synonym of a word out of a list of alternatives. In order to do that, the system will approximate the semantic similarity of any pair of words.The semantic similarity between two words is the measure of the closeness of their meanings.
For example, the semantic similarity between “car” and “vehicle” is high, while that between “car” and “flower” is low.
The algorithm implemented in this project had an accuracy between 67.5% and 72.5%.