1. Algorithms of POS Tagging
HMM (generative)
Maximum Entropy Markov Model (discriminative)
Conditional Random Field (discriminative)

2. Three Fundamental Problems of HMM
1. Statistical Inference of the State Sequence Find P(S|O) by Viterbi Algorithm
2. Observation Determination
Find P(O|S) by Forward Algorithm, Backward Algorithm
3. Model Estimation
Given S,O estimate model parameters (Transition and Emission probabilities) by Baum-Welch
Algorithm (based on Expectation Maximization)

3. HMM Examples HMM Classic Example NLP Example
(Urn Problem) (POS Tag Example)

4. URN Problem ^ R G B $ - Observation Seq U3 U3 U3 U1 U1 U1
U0 U2 U2 U2 UF
U3 U3 U3
Trellis or Stak Graph . . . . . .

5. POS Tag Problem J J J ^ People Jump High $ - Observation Seq N N N
^ V V V $
J J J
Trellis or Stak Graph . . . . . .