Student Career Recommendation System Using Content-Based Filtering Method
Adib Hakimi Abdul Rashid, Masurah Mohamad, Suraya Masrom, Ali Selamat
Abstract
The most frequent difficulty that graduates face is finding a suitable profession. Finding a job after graduation might be challenging for students who are unsure about their future goals. The goal of this project is to create a system that only recommends careers for students studying computer science. Web scraping was used to extract the career information from the JobStreet website. The recommendation is made using a content-based filtering technique that compares one thing to another based on the user's preferences. The user can easily make recommendations using the system's user-friendly interface and straightforward instructions. Using a specialised functionality tester, this system was put through its paces and more career opportunities will be offered to career vacancy websites in the future. In addition, the system will be more sophisticated when it comes to narrowing down the pool of potential careers that the user can choose from, and it will be directly linked to career page websites to guarantee that all open positions are still open for the user to apply for.