Comparative Analysis between Naïve Bayes Algorithm and Decision Tree to Solve WSD Using Empirical Approach

There are many robust approaches algorithms for Word Sense Disambiguation using machine learning, and it is very difficult to make comparisons between them if we don't implementation empirically. In this word, analysis and developed JAVA Code and compare between two of the most successfully approaches for supervised machine learning, namely, Na ve Bayes and Decision tree using WordNet and Senseval3 for Word Sense Disambiguation of words in context.