Comparing Various Machine Learning Algorithms for User Recommendations Systems
Rahul Dev Garg, Shivay Lamba, Sachin K Garg · 2021
Recommending users on the basis of various user preferences while interacting with a social media platform, such as the gender, age, number of meetups, the skills and ratings of user profiles, image quality. All are taken into consideration to provide the ultimate user recommendation possible to make the software more relevant and user centric with recommendations strictly based on the way a given user interacts with the platform. Several machine learning algorithms have been used such as Neural Networks, random forests, linear regression to compare which provides the best possible recommendations for a user. Specifically, a weighted social interaction network is first mapped to represent the interactions among social users according to the gathered information about historical user behavior.