With the ever-growing volume of online data, recommendation systems have been an effective way to solve the prominent problem of information overload. Over the past few years, we have witnessed the success of deep learning in various domains, such as computer vision and natural language processing (NLP). This allows for tremendous advancements to the recommendation systems we know today.
This whitepaper delves into the development and evolution of recommendation systems, and how they have become highly integrated and essential in today’s digital economy. We will also shine the spotlight on a leading recommendation system, BytePlus Recommend, to overview how it is applied in various uses today. The content within is specially tailored for engineers, system architects and data scientists who want to understand how an industry-leading recommendation system works in practice, as well as the key considerations they need to make when deploying a recommendation system.