A WEB BASED APPLICATION FOR ANIME RECOMMENDATION SYSTEM USING CONTENT-BASED FILTERING ALGORITHM

Abstract

In this study, the author introduces "Cpython," a web-based platform that employs a Content- Based Filtering Algorithm to deliver personalized anime recommendations to users. The

application is strategically designed to provide a solution that aids anime enthusiasts in navigating the vast array of available anime titles. This research entails a comprehensive outline and implementation of the application, which includes the incorporation of an administrative panel feature for seamless management of anime-related data. Furthermore, this investigation conducts a thorough assessment of the system's performance to ensure that the generated anime suggestions genuinely resonate with and satisfy users. "Cpython" aspires to offer an inventive remedy for anime aficionados who frequently grapple with the overwhelming abundance of anime selections at their disposal. The application's objective is to elevate the user experience and furnish superior guidance for selecting anime in accordance with individual preferences. This research also holds potential impact in the development of content-based recommendation systems applicable to various domains beyond anime. With the technology utilized and methodologies implemented, "Cpython" serves as a tangible example of how technology can be employed to address complex challenges in delivering relevant recommendations.