What it does
It treats each article released on the internet as a matrix, it's elements are weighted by the preference of information from the users. Allowing us to perform linear algebra and matrix manipulation over hundreds of articles collected to arrive at a "significance score" for each day. If this score does not pass the set limit, the day will be deemed as news white noise, else, it is viewed as relevant and AI was used to summarize key articles for users to read.
How we built it
We used node.js, express-sessions, bootstrap for web development. On the data handling side, we used Natural Language Toolkit (nltk) from Python to do analysis and linear algebra
Challenges we ran into
Front end took too much time, and we had to do approximation of linear algebra for the significance score
Accomplishments that we're proud of
Putting out a demo in 2 days that encapsulates what we are trying to do
What we learned
To respect front end development more
What's next for Clear Signal
refining the application, collecting more data for a more accurate significance score, and research on refining our math pipeline.
Log in or sign up for Devpost to join the conversation.