ScholarsAid: A Personalized Scholarship Web Application based on Web Scraping
Abstract
In today's digital age, finding relevant scholarship information has become a major challenge for students. The current process of identifying and selecting scholarships is both time-consuming and decentralized. To address this issue, this paper presents the fundamental design and implementation of a web application that leverages web scraping techniques to provide personalized scholarship recommendations to students. The web application is developed using the Rapid Application Development (RAD) model and covers the entire process from data collection through to evaluation of the personalized scholarship recommendations. The application allows students to easily search and filter scholarships based on their specific needs or preferences, and utilizes a matching algorithm to provide the most relevant scholarship options. The web application offers functionality for students to search and filter scholarships to suit their preferences or needs and the most relevant scholarships are provided based on matching algorithm. With this web application, students can make more informed decisions and take a step towards achieving their academic goals. The development of this web application has the potential to revolutionize the way students search and apply for scholarships. Moreover, the application can also benefit scholarship providers by making the selection process more efficient and targeted. In addition, the web application can contribute to the broader social and economic benefits of higher education.
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