Submitted at HackHarvard 2018. Worked with Elliott Lehrer, Donnie Sahyouni, Andrew Liu, and Evan Velasquez (Brown '21)

Inspiration

We are computer science students with large ambitions and little time. It just takes far too long to get an effective understanding of a large body of text. We know this problem is not exclusive to us, so we wanted to create an application that alleviates this issue and saves time for busy readers everywhere.

What it does

Our application can parse a pdf or txt document and uses our word and sentence rating algorithm to generate a short and effective summary of the piece, capturing only the most important points in less than 5% of the time.

How we built it

We used Java in the backend along with the Aliasi natural language processor to do the dirty work, and we use JavaFX for the actual application.

Challenges we ran into

It turns out to be quite difficult to build a website. We struggled with natural language processing, as pdf parsing is imperfect and can sometimes run into problems with many frameworks that work with raw text. Ranking summary sentences is complicated, and requires intricate planning to result in effective information.

Accomplishments that we're proud of

We have a functioning JavaFX application that is easy to use and saves your everyday college student countless hours in reading and studying.

What we learned

We learned how to use JavaFX and how to effectively gauge summary sentences. We learned effective task management, and responsibility delegation.

What's next for Skim

This as a website is infinitely more convenient for our target audience. Our goals are to get this fully online and available to as many people as possible.

Built With

• aliasi
• java
• sweat-and-tears