Track: Best Beginner
Inspiration
We first thought about making our own algorithm for TikTok, but we realized that it was too time consuming for our allocated time. We branched off this idea to make a recommendation system for UCR's clubs. This is how we arrived at this conclusion to do the project.
What it does
It find's student organizations at UCR based on similar keywords that the user provided. It will used sentence transformation to compare keywords that are similar instead of matching the exact keywords.
How we built it
We built it using Git as our version control system, Python as the backend server, and regular HTML, css, and JS for the frontend which also talks to the backend. We also packaged everything in a docker image that will make deploying on the cloud or anywhere else much easier.
Challenges we ran into
We had a hard time first brain storming our project idea as we had 3 ideas that we were considering. We also had trouble connecting frontend to backend. Another challenge we had was finding a method of student org recommendation as well as a way to convert clubs and their descriptions to a dataset.
Accomplishments that we're proud of
We were successfully able to create the recommendation system for our project using sentence transformation. We are also proud of using flask and fetch api to connect our front and backend code. We are also proud of the design and look of our web app.
What we learned
While working on this project, our team learned how to work as a collective and resolve issues over differing methods of programming. We also learned how to divide roles while still working as a team to work around everyone's strengths. We also learned how to wisely allocate our time to work on different sections of our project.
What's next for Highlander OrgQuest
We plan to upscale our project to work with larger datasets such as all the student organizations at UCR. In the future we also would like to include descriptions as well as key links with our recommended orgs. Another thing we could change in the future would be to allow user inputs of sentences as well as key phrases. One last thing that we could add is a process of converting club descriptions to keywords inside our database instead of inputing the keywords manually.
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