We wanted to create something that can help users more quickly visualize data and draw connections to explore topics that they might not have noticed was related to their initial topic.

What it does

VSearch will visualize data by parsing through thousands of weblinks on a given topic, drawing connections, evaluating importance, and constructing meaningful abstractions to help users better understand surrounding topics.

How I built it

We used python to build a scraper that scrapes academic resources and then make connections between these resources based on the the content. We serve this data using Express.js and visualize it on the UI using d3.js

Challenges I ran into

Data scraping was extremely resources intensive. Cross code collaboration.

Accomplishments that I'm proud of

Each member of the team was able to focus entirely on what they are most capable of and we were all able to collaborate and combing each of our different parts together and work successfully.

What's next for VSearch

The next step for VSearch is to implement natural language processing to better draw connections(example, a dog & a poodle would result in a connections). We can also filter connections based on topics and types.

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