Intersection

Project for the course Multidisciplinary Project in the academic year 2022-2023 at Politecnico di Milano, made by:

• Alberto Noris (@AlbertoNoris)
• Nicole Perrotta (@NicolePerrotta)
• Alberto Pirillo (@albertopirillo)
• Andrea Sinisi (@AndreaSinisi)

Supervised by Dario Chiossi ([email protected]).

Description

This repository contains the source code for a website that leverages Artificial Intelligence to match workers and companies. The goal is 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 their gender, 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 can 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 was built using the following technologies:

• Front-end: HTML, CSS, JavaScript, Bootstrap
• Back-end: PHP, Python libraries (FastAPI, pdfplumber, SQLAlchemy, PyTorch, and Poetry)
• AI Model: Transformer-based Bi-encoder (Reimers & Gurevych, 2019)
• Database: PostgreSQL
• 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.

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

We appreciate your interest in the project!