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Job-Hunting-WebScraping (Job Harvest)

📌 Overview

Job Harvest is an intelligent job search platform that aggregates job listings from multiple renowned portals using web scraping and enhances search accuracy with Natural Language Processing (NLP) and a Recommender System. The platform provides multilingual support, abbreviation expansion, and personalized job recommendations, making job hunting more efficient and accessible.

🚀 Features

  • Aggregates job listings from platforms like Drjobs, Tanqeeb, Jobzella, Forasna, and Wuzzuf.
  • NLP-powered search enhancement (abbreviation expansion, keyword normalization, bilingual support).
  • AI-driven Recommender System for personalized job suggestions.
  • Real-time scraping automation with APScheduler.
  • User-friendly web interface built with TypeScript, JavaScript, CSS, and HTML.
  • Seamless API integration with a Supabase backend.

🛠️ Technologies Used

  • Python (for data processing, automation, and AI integration)
  • BeautifulSoup & Selenium (for web scraping)
  • NLTK & SpaCy (for NLP preprocessing)
  • T5-based NLP Model (for abbreviation expansion and contextual understanding)
  • Google Translate API (for bilingual job search support)
  • APScheduler (for scheduling automated scraping tasks)
  • TypeScript, JavaScript, CSS, HTML (for front-end development)
  • Supabase (for database and hosting)

🔧 Installation

Prerequisites

Ensure you have the following installed on your system:

  • Python 3.8+
  • Node.js & npm (for front-end development)

📌 Usage

  • Search for jobs using natural language queries (e.g., "ML Engineer in Cairo").
  • Get personalized recommendations based on your profile and previous searches.
  • Apply for jobs directly through aggregated listings.
  • Filter and sort jobs based on various criteria (e.g., industry, location, experience level).

👥 Team Members

  • Mohammed Tarabay
  • Samir El-awady
  • Mohammed Rizk
  • Adham El-Sadat
  • Sami El-Yazouri
  • Ahmed Eltabal
  • Ashraf Salah
  • Ahmed Zien

📜 License

This project is licensed under the MIT License – see the LICENSE file for details.

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