Cloudsuggest: Enhancing E-Commerce with Personalized Recommendations

Abstract

This review explores the impact of cloud computing on the development of artificial intelligence (AI) in the ecommerce sector, focusing on the advantages and challenges of their integration. It also examines how cloud-based AI technologies have transformed customer assistance, inventory management, fraud detection, and supply chain optimization. The paper also explores potential advancements and business opportunities that could result from the integration of AI and cloud computing in e-commerce. Literature has the potential to transform and offer an escape from daily life, with systems for book recommendations using algorithms like collaborative filtering, content-based, and association criteria. These systems provide personalized suggestions based on users' preferences and reading histories, enhancing the reading experience in the digital age. A strong technique for exact suggestions is created by fusing collaborative filtering with neural networks to merge content. Collaboration and real-time dynamics are emerging themes to address information overload and enhance user experiences in online applications. These trends enable collaborative and dynamic recommendations across devices and the cloud, optimizing suggestions by recognizing various data distributions. The Intelligent Device-Cloud Parameter Request Model (IDEAL) is proposed to address this issue by evaluating request revenue with little resource consumption, enabling adaptive and revenue efficient device-cloud communication.