Personalized Job Opportunity Finder powered by Web Scraping

Department of Computer Science and Engineering, Vardhaman College of Engineering (Autonomous), Hyderabad, India.

^* Corresponding author: budharapuakshay@gmail.com

Abstract

"Personalized Job Opportunity Finder powered by Web Scraping" research presents a comprehensive exploration the development and implementation of an innovative Job Portal, aiming to redefine the traditional job search experience. The project leverages cutting-edge techniques and integration with prominent communication tools. The experimental setup involves meticulous web scraping from renowned job portals, Google and Apple, using Puppeteer and Cheerio for data extraction. The user interface is thoughtfully designed, featuring an intuitive registration form and a dynamic home page that showcases personalized job recommendations. The research delves into the advantages of scraping job data from top companies, showcasing its efficacy compared to traditional methods such as partnerships and direct job postings. Big companies such as Google, Apple and Meta don't use partnerships for most of its hiring, that makes it difficult for candidates who aspire careers at such companies. Direct partnerships may have delays in updating job listings, whereas scraping allows for more immediate access to new postings.