ezA

• 

  e(ric) z(aid) a(ndrew, jay)

Inspiration

Current classroom boards have poor search functions. We wanted to implement a search that intelligently looks for answers to a student's question.

What it does

Our search function looks to narrow down search results by finding potential answers in files uploaded by the professor and in previously answered questions.

How we built it

We used bootstrap for front-end, flask and pymongo for back-end, google-cloud natural language processing for answer search, and various python libraries for other necessary tasks such as web scraping.

Challenges we ran into

It was very difficult to parse through text in an html file and determine what text represents relevant information worthy of being saved to a database.

Accomplishments that we're proud of

We are extremely proud that we all contributed to the project and learned a lot about new software api's and technologies. We also think our project idea has great potential.

What we learned

We learned a ton about how to make a web application. We got a lot of experience with front-end, back-end, and utilizing many useful api's.

What's next for ezA

We are going to perfect our software to make the search more efficiently and accurately find answers from course files and discussion posts.

Built With

• bootstrap
• flask
• google-cloud
• mongodb