PoKED: A Semi-Supervised System for Word Sense Disambiguation

Word sense disambiguation is branch of Artificial Intelligence (AI) which deals with the Natural Language Processing. Word sense disambiguation deals with the polysemy of word, in natural language processing a single word are having two or more meanings where respective context discriminates the meaning. Human beings are quite intelligent to get meaning of the word as they are having biological neural network. Computers can be trained in such a way that they should work same as biological neural networks. There are different suggested approach for the disambiguation such that knowledge-based, supervised, semi-supervised, and unsupervised. The objective of this research is to improve better communication in between the computer and human being. The discussed model used supervised learning approach with linked allocation for calculating word space and tree approach for word sense