UCR SP Search is a project designed to automate the process of categorizing university courses based on their alignment with the United Nations' 17 Sustainable Development Goals (SDGs). The system analyzes course descriptions and predicts whether a course is “sustainable” and which SDG it aligns with. For example, if a course focuses on reducing economic disparity, it would be classified under SDG 1: No Poverty. This project helps universities identify and promote courses that contribute to sustainability, which can lead to increased funding from organizations like the UN.
Authors:
Sachina Chopra, Peter Lu, Melissa Castro, Daniel Yao
- Flask: For our Backend API and server-side logic.
- Elasticsearch: To index and search course data efficiently.
- PostgreSQL: For managing and storing course data.
- Docker: Used for containerization and to run Elasticsearch
- Next.js: Building the client facing UI.
The project aims to streamline the process of classifying university courses into sustainable development categories, helping universities showcase their contribution to sustainability goals. The long-term goal is to enhance the accuracy of SDG alignment predictions using machine learning and natural language processing (NLP) techniques.
ELASTIC_SEARCH_API_ENDPOINT=
ELASTIC_SEARCH_API_KEY=