Our inspiration for mathify came from the fact that often times we need help from our friends when solving difficult math problems. The challenge arises when we try to text our friends and there is a lot of confusion due to not being able to properly use mathematical notation.

What it does

Our hack takes natural language user input and converts it to a png with proper math notation which can be shared via text message.

How I built it

Our coding was done entirely in Java, and we implemented many LaTeX java APIs, such as JLatexMath and JMathText. Additionally, we used ArrayLists and document parsing for the actual translation of natural language.

Challenges I ran into

One of our main challenges was finding the proper LaTeX APIs as many of the APIs online did not function as advertised.

Accomplishments that I'm proud of

We were able to create a program which relied more on just stack overflow and required more independent thinking, something we have not experienced as beginner programmers.

What I learned

We learned how to manipulate data, such as user input, as well as the basics of natural language processing. Additionally we learned how to implement various APIs and bringing them together to create a program.

What's next for Mathify

Currently, Mathify is a proof of concept that natural language can be processed and translated into math. We want to take it to the next level by first taking our desktop program and creating a fully functioning mobile app so users can share easily with their friends directly from their phones. Additionally, in the future, we would like to implement some sort of AI which can translate all sorts of natural language and potentially use some form of machine learning to learn more about users over time.

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