Project
1. Introduction and Background - 10%
- General Background:
- What is the general background of the problem you are working on?
- Specific Problem:
- Under the general topic, what specific problem is your project addressing?
2. Motivation and Objective - 10%
- Problem Statement:
- What are the limitations of existing methods in addressing this problem?
- Contribution and Novelty:
- Given the previous limitations, what is your unique contribution, and how does it provide novelty in solving the problem?
3. Data Collection and Analysis - 30%
- Dataset:
- What dataset are you working on to solve the problem?
- Dataset Introduction and Analysis:
- Provide a basic introduction to and analysis of the dataset.
4. Method - 30%
- Algorithm Design/Implementation:
- What data mining/machine learning algorithms are you designing or applying to tackle the problem?
5. Experiment and Discussion - 20%
- Experimentation:
- Conduct experiments to verify that the proposed method works.
- Discussion:
- Analyze and discuss the results of the experiments.
Here is an example of one-course project.