Major Way

• 

  Major "Wei"

Inspiration

Based on personal experience of enrolling in STEM majors. Once enrolled, students like us were blindsided with courses that had intricate course names. Who knew that computer science requires so much math? Well, we found that out the hard way. If only other students like us who dream of pursuing STEM majors could use a service that outlines all the different areas of study that they'll encounter in their major. Oh wait, now there is!

What it does

Major Way parses in the four-year curriculum of the user’s intended major, and extracts all the courses and scans through their respective summaries using the Wikipedia API to generate intersection graphs of the most relevant subtopics to the field to finally tally them all up into a simple pie chart.

How we built it

Utilizing Wikipedia API and SPARQL queries to extract data from DBpedia to create the semantic relationships, we developed our own homemade natural language processing (NLP) algorithms for the backend. We trained our NLP by scraping Wikipedia's article of “Outline of academic disciplines” and DBpedia. The result is then outputted as a JSON file that is used to feed the data into a colorful and descriptive pie chart.

Challenges we ran into

The mathematical part of the graph intersection was challenging for us. In addition, to debating which data structure to utilize (in the end we worked with dictionaries and arrays).

Accomplishments that we're proud of

Successfully developing a working natural language processing algorithm.

What we learned

We got in depth with graph theory and furthered our Javascript to develop the project.

What's next for Major Way

To expand and improve our parsing pipeline for the system, optimize our intersection graph, and learn more JavaScript for a better UI to get the user more details on the output.sq

Here's a link that shows a page-by-page breakdown of our project

Built With

• python
• javascript
• bootstrap
• data-sicence
• natural-language-processing
• flask
• jquery