Natural Language Processing assignments and Project
HW #2
Assignment2 Q2 Program to compute the bigram model (counts and probabilities) on the given corpus (HW2_F17_NLP6320-NLPCorpusTreebank2Parts-CorpusA.txt)under the following three (3) scenarios: i. No Smoothing ii. Add-one Smoothing iii. Good-Turing Discounting based Smoothing
Assignment2 Q3_Q1 Transformation-based POS Tagging: Implemented Brill’s transformation-based POS tagging algorithm using ONLY the previous word’s tag to extract the best transformation rule to: i. Transform “NN” to “JJ” ii. Transform “NN” to “VB”
Assignment2 Q3_Q2 Program to compute the bigram models (counts and probabilities) required by the above Naïve Bayesian Classification formula.
HW #3
Implemented the Viterbi algorithm to compute the most likely weather sequence and probability for any given observation sequence. Example observation sequences: 331, 122313, 331123312, etc.