Team Project

The course project is an opportunity to apply data mining algorithms to real-world problems and/or to prepare students for data mining research. The objective is to engage in the full spectrum of data mining process to discover data-driven knowledge and support data-driven decision-making. 

Topic

The project topic is open-ended such that each team can apply existing data mining techniques or propose new data mining techniques to address a real-world problem. Each team is free to choose any problam and "good" dataset for data-driven analysis. Project teams are encouraged to use existing real-world datasets or crawl data from the web if fitting. 

Teams

Students will work in 2 - 3 person teams. Diversity in backgrounds, skillset, and interests is important to conduct a strong and successful project. 

Milestones

There are 4 main components of the project that will be due at various points during the semester:

• P1 - Dataset Discovery & Evaluation [Individual]: Identify a potential dataset of interest for individual exploration; conduct formal exploratory data analysis (EDA) and data pre-processing to evaluate the richness and potential of this dataset to answer interesting questions.

• P2 - Scope Definition & Literature Review [Team]: With your team, decide on your project dataset(s) and the target scope for your project (i.e., what key questions will this project set out to answer); conduct a literature review to outline related work in your domain of choice, potential gaps and opportunities to move the needle.

• P3 - Implementation & Midway Check In [Team]: Conduct your analysis to answer the key questions you identified with the dataset(s) you have selected. Seek to uncover insights that can support data-driven decision-making (i.e., you should be able to answer why is this insight important?)

• P4 - Final Report & Presentation: Write a research-grade paper and complete a final presentation to communicate your project work, analysis, and findings with the broader community.

Deliverables

Each team is expected to document and report on all project components (P1 - P4).

The final portfolio (P4) will include a:

1.  Final Report: ~5 pgs for a 2-person team or ~7 - 8 pgs for a 3-person team, excluding references and appendix (if any). All reports should be written using the IEEE transactions journal template which is available here or directly from Overleaf.

2. Final Presentation to communicate the full data mining journey including the research problem, analysis approach, and findings.