Nanos gigantium humeris insidentes!

## Two project topics

**Equivalence between Reductive English and FOPC**

- Labeled as: Eq RE & FOPC
- Description: From the aspect of logic or math, prove that the FOL has the same expressive power of the converter I design
- Related knowledge:
- Theory of FOPC / logic
- Psychology
- Language
- Turing machine

- Pros and Cons
- It’s a theoretical problem
- It’s a good novel aspect
- It might be too difficult
- It might be even not correct

- Evaluation
- Academic Value: ▲▲▲▲△
- Feasibility:▲▲△△△
- Difficulty: ▲▲▲△△

**Semi-supervised Learning on NLP**

- Labeled as: ML on NLP
- Description: Improvement or Implementation of
*Semi-supervised Semantic Role Labeling Using the Latent Words Language Model* - Related Knowledge
- Machine learning
- NLP

- Pros and cons
- It’s popular research field and match lots of researcher.
- The potential professors options are greater.
- I don’t have enough background knowledge for semi-supervised Learning.

- Evaluation
- Academic value: ▲▲▲△△
- Feasibility: ▲▲▲▲△
- Difficulty:▲▲▲▲△

**Probabilistic disambiguation:**

- Labeled as: PD
- Description: P1, the context-free probability of a meaning to a word W; if given probability P2 to word W2. Then the joint probability is P(E1|E2)
- Related knowledge
- Probability
- Syntax and Grammar

- Pros and Cons
- It’s a theoretical problem
- It looks like obvious works
- There is some work.

- Evaluation
- Academic value: ▲▲▲△△
- Feasibility: ▲▲▲▲△
- Difficulty:▲▲▲△△

Comparision: Project 2 vs Project 3 Projct3 is vague and would be part of Project 2, thus ruling out Project 3.