Current Members: Ziwei Gu (CS/Math '21), Xinqi Lyu (CS '20), Nikhil Saggi (CS '21), Eric Sun (CS/Stats '20), Debasmita Bhattacharya (CS '21), Ellen Chen (CS '20)
Past Members: Jim Li (M.Eng '18), Linnea May (CS '21)
Objective: To model the structure of knowledge on Wikipedia and provide recommendations for a path of learning based on a certain inputted topic.
When learning a new topic, there are two particular challenges one can face:
- Upstream knowledge: The user wants to learn a new topic, but doesn't know where to start. For example, a user might want to know how Principal Component Analysis (PCA) works, but they don't know what topics are prerequisite to their understanding.
- Downstream knowledge: The user knows the basics of a topic, but wants to learn more. For example, a student has finished their first Linear Algebra course and they want to discover ways they can apply their knowledge.
We aim to solve both these problems and provide a customized path of learning for any user by analyzing the network and similarities of Wikipedia articles and generating a new graph-based visualization.
