Mind Map Automation: Using Natural Language Processing to Graphically Represent a Portion of a U.S. History Textbook

Abstract

A mind map is a hierarchical representation of ideas that can be branched back to one centralized theme. Mind mapping can be applied to many disciplines and provides numerous cognitive benefits. One problem, however, is that the process of creating a mind map can become tedious and time consuming. This is especially problematic for students who have busy schedules and need to optimize their studying time. Therefore, this thesis aims to solve the challenge by developing an automated mind mapping system to analyze sections of a U.S. history textbook. The system uses natural language processing techniques to organize the text so that it can be graphically displayed for users. The primary goal of this project is to give students a supplementary tool that they can use to further their studies, and a future objective of this research is to expand the scope to include subjects outside of U.S. history.