Multirec: The Three-in-One Recommender
We have been assigned to do a small project based on our ideas and knowledge. Our team decided to build a multimedia recommendation system. We aimed to build a movie recommendation system, but we added two more media recommendation systems, they are music and game. Young people nowadays have access to video games, movies, and music. We knew platforms that already have recommendation systems and can play the media. However, our website recommends which type of movie the user can watch, which music they can listen to or the game they can play. Designing the website needs the design concept for the website, the understanding of the front-end which mainly includes the design of the webpage. Understanding the back end is a vital part as the entire recommendation system would work with the backend code. After researching thoroughly, we found that we can build the front-end using CSS and HTML-5, and the back end can be coded using python. After finding that the same layout could be built for more than one type of media, our team decided to include music and games. The database, which contains information about the movies, music, and games, was discovered on the internet. There are certain limitations to the project. We cannot make a recommendation system for every type of media. Artificial intelligence will not be used to its full extent in our recommendation system. The recommendation system will be using the statistics and the information provided in the database to recommend the user of the media they search recommendations for. This recommendation system will help us in understanding how the database is linked to the program that has been created; it will also help in understanding the basics of coding. This building of knowledge will help us in understanding how this recommendation system or another type of programme can be improved in the future.
Keywords - Recommendation System, Statistics, Database, Python