Enhancing Mobile Roommate Matching with Artificial Intelligence Algorithm: A Progressive Framework

This paper addresses the pressing issue of university student housing by offering a range of functions. Users can share information, search for matches based on preferences, and narrow down options by institution name and address. Finding a compatible and safe roommate can be challenging, but our platform aims to pair individuals based on their personalities. This empowers users to select potential roommates with insight, ultimately enhancing their living situation and fostering lasting connections. In the current situation of escalating housing costs, locating a suitable living space that aligns with one's budget, preferences, and proximity is particularly challenging for students. While there are various websites and mobile apps designed to help find roommates and available apartments, there is currently no dedicated smartphone app for a specific university. In addition to the mentioned features, we have integrated a Machine Learning approach, accompanied by a visual analysis illustrating its flow. This innovative inclusion bolsters the platform's ability to intelligently match users, further streamlining the roommate selection process and ultimately contributing to improved living situations and enhanced security.