Access Job Recommendation System

Project Domain / Category

Web based Application

Abstract/Introduction

The Access Job Recommendation System is an AI-powered web application designed to help job seekers find relevant job opportunities based on their skills, education, and preferences. The system utilizes machine learning algorithms to recommend personalized job listings and offers features like resume parsing, real-time job alerts, and application tracking. Admins can manage job listings, monitor user activity, and ensure system efficiency. The project aims to improve job search efficiency by providing intelligent, automated recommendations while ensuring data security and privacy.

Functional Requirements

1.  Job Seeker Functionalities

·         User Registration & Login: Create an account and log in securely.

·         Profile Management: Upload resume, add skills, education, and experience.

·         Job Recommendations: View AI-powered job suggestions based on the profile.

·         Search & Filter Jobs: Search by keyword, category, location, and salary range.

·         Job Alerts & Notifications: Receive real-time job postings via email or in-app notifications.

·         Application Tracking: Track applied jobs and their status.

·         Bookmark Jobs: Save job listings for future reference.

2.  Admin Functionalities

·         Admin Dashboard: View system analytics and user activity.

·         Job Posting Management: Add, update, or delete job listings.

·         User Management: Approve, suspend, or delete users.

·         Monitor System Logs: Track user interactions and application logs.

·         Review & Improve Recommendations: Monitor AI performance and fine-tune algorithms.

Recommended Tools for Development Frontend:

HTML , CSS, Javascript (any framework like React, Vue or Angular)

Backend:

·         Node.js with Express.js

or

·         Django (Python)

Database:

·         PostgreSQL / MySQL