E-commerce Trend Prediction Software

In the modern-era of technology, there is an immense boom of e-commerce business and e-commerce powered SAAS. It includes building robust services and good exchange with the internet. Therefore, the Recommendation Systems is one method to reorganize and restructure the overload of information on basis filtering and bifurcation methods. This article will illustrate a comprehensive Literature Survey regarding the published papers in the field of e-commerce recommendation systems, which will help the researchers and Software Engineers to do future work. We provided the varieties of traditional techniques followed to build such recommending systems and the challenges faced during creating such recommendation systems. In this review we analyzed various different recommendation algorithms and a potentially improved model is proposed. Building the Recommendation system is a challenging task, as it involves the problems of data sparsity and scalability requirements. Recommendation systems are crucial for E-commerce business, it provides personalized recommendations to the customer. Software Engineers and researchers can play a vital role in building and improving such recommendation systems by understanding its traditional techniques, challenges and future directions.