Intersection

Project for the course "Multidisciplinary Project" made by Alberto Nori (@AlbertoNoris), Nicole Perrotta (@NicolePerrotta), Alberto Pirillo (@albertopirillo) and Andrea Sinisi (@AndreaSinisi) related to the 2022/2023 academic year at Politecnico di Milano and supervised by Dario Chiossi ([email protected]). This is the link of the online web site: https://intersection.up.railway.app

Description

This repository contains the source code for a website that leverages an AI model to match workers and companies. The website aims to facilitate the process of connecting job seekers with suitable job opportunities.

Features

• Worker Profile Creation: Workers can create profiles by uploading their CVs and providing personal information such as the gender, the birth date or the country they come from
• Company Profile Creation: Companies can create profiles by providing information such as the country they come from or their description
• Job Offer Posting: Companies can post job offers, specifying the salary, the duration and the job description
• AI Matching Algorithm: The website relies on an AI model to analyze worker CVs and job offers, providing personalized recommendations and identifying potential matches based on skills, experience, and other factors
• Interactive Interface: The website offers a user-friendly interface, allowing workers to browse and apply for job opportunities, and companies to review worker profiles and select suitable candidates
• List of Job Offers: Workers have the ability to view job offers ranked according to their relevance as computed by the AI model, while companies can access a ranked list of applications to their job offers, also determined by the AI model

Technologies Used

The website is built using the following technologies:

• Front-end: HTML, CSS, JavaScript, Bootstrap
• Back-end: PHP, Pyhon libraries (FastAPI, pdfplumber, SQLAlchemy, PyTorch and Poetry)
• Database: PostgreSQL
• AI Model: Bi-encoder from Sentence Transformers library
• Deployment: Railway

Setup and Configuration

To set up the website locally, follow these steps:

• Clone the repository to your local machine
• Set up a web server environment (such as Visual Studio Code) and configure it to run PHP
• Import the database schema
• Configure the database connection settings in the appropriate PHP files
• Set up and configure the API:
  • Install Python 3.9 and Poetry
  • In the folder "AI Algorithm" run the command poetry install
  • Update the API address with the local one in the back-end pages
  • In the folder "AI Algorithm" run the command uvicorn api:app to run the API
• Start the web server and access the website through a web browser

License

Licensed under MIT License.

---

If you have any questions or suggestions regarding the website or the repository, please feel free to contact the contributors.

We appreciate your interest to the project!