CornellDataScience/Wikipedia

Name: Wikipedia

Owner: Cornell Data Science

Description: Project for the Data Visualization subteam during SP18. Visualizing the hierarchical relationship of knowledge on Wikipedia.

Created: 2018-03-17 19:21:58.0

Updated: 2018-03-17 20:20:20.0

Pushed: 2018-03-21 23:05:01.0

Homepage: null

Size: 1600

Language: null

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README

Wikipedia

Members: Jim Li (M.Eng '18), Linnea May (CS '21), Nikhil Saggi (CS '21), Xinqi Lyu (CS '20), Ziwei Gu (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:

  1. 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.
  2. 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.

Prototype Visualization

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This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.