## Overview
The Employment Referral System presents an innovative approach to job recruitment by streamlining the process using advanced technology. Leveraging machine learning through Spark ML and collaborative filtering, this platform aims to enhance the matching of job seekers with potential employers. The system is designed as part of a graduation project, showcasing the application of big data technologies in real-world scenarios, particularly in the hiring landscape.

## Features
- **Machine Learning Integration**: Utilizes Spark ML to optimize the recommendation of job opportunities for candidates based on their profiles and preferences.
- **Collaborative Filtering**: Implements sophisticated algorithms to analyze user behavior and preferences, delivering personalized job suggestions to users.
- **Data Scraping**: Capable of extracting job postings from various sources such as Zhaopin, ensuring users have access to the latest job openings available in the market.
- **User-Friendly Interface**: Designed with a clean and intuitive interface that allows users to navigate through job listings effortlessly.
- **Real-Time Updates**: The platform provides real-time data updates, ensuring that job seekers have the most current information at their fingertips.
- **Graduation Project Innovation**: As part of a graduation project, it reflects the practical application of theoretical knowledge in a crucial industry.