With how often news stories are created and updated, it can be a struggle to keep up with the latest news. Stories get new additions added daily and sometimes the details of the entire story are dispersed across multiple articles and multiple publications.

What it does

TL;DR analyses a constant incoming feed of news articles and develops a notion of "trending stories" from this. It then finds other articles that are also part of the trending stories and consolidates (summarizes) the articles into one summary. The summary is then presented to the user so that they can quickly understand the relevant information from a story.

How we built it

The backend is a Java/Springboot web service hosted on Heroku with a ClearDB database instance. The front end is an Android app.

Challenges we ran into

The sheer amount of data we had to process taxed our web services as well as the APIs we used to do some of our business logic. Additionally towards the end of the project we took down our database instance. Many of us had very limited programming experience, and none of us had any Android app development experience.

Accomplishments that we're proud of

We were able to get a web service that (for a period of time) was able to generate summaries for trending topics based on a corpus of news articles. We were also able to render these summaries on an Android app.

What we learned

What's next for TL;DR

Subscribing TL;DR to a live feed of news articles would allow the project to provide an actual service to people today. Additional features include ensuring only a subset of articles are stored in the database, and for the database to be regularly purged, so that we do not need to hold on to gigabytes++ of data.

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