In the digital age, information overload has become a significant concern.
This refers to the overwhelming amount of data available, which exceeds what users can effectively manage and complicates decision-making processes.
The issue arises when systems fail to handle and process large volumes of data efficiently.
For instance, in many e-commerce platforms, users are often presented with numerous options but have limited time to explore them.
Recommendation systems, a powerful solution to this problem, aim to address information overload by simplifying choices for users.
Over time, Recommendation systems (RSs) have faced a consistent set of challenges that are crucial to consider when discussing both
new and traditional approaches.
In this book, an overview of the most common challenges is considered, encompassing pure-cold start, data sparsity, cold start, first impression metrics, and scalability.
Strategies to mitigate these challenges can significantly boost user engagement and retention which is the ultimate goal of the business.
