Deep Learning-Based cloud services recommendation
Saida Kichou, Brairi Ismail, Essalhi Mohamed Amine · 2024
With the exponential proliferation of cloud service platforms, the task of discovering relevant cloud services becomes increasingly challenging for users. In this work, a novel approach for cloud service recommendation that incorporates both social feedback from user comments and an innovative Auto-encoder model is presented. Leveraging the insights obtained from user interactions, our solution aims to enhance the accuracy and effectiveness of service recommendations within cloud computing environments. Through rigorous experimentation, we demonstrate the efficacy of our approach in accurately predicting user reviews and delivering adapted service recommendations that align with user preferences and requirements. Our performance evaluations underscore the solution’s robustness and its ability to meet the evolving needs of users in cloud-based systems.