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
The development and refinement of recommendation systems play a pivotal role in providing tailored content and product suggestions to users.
However, despite their wide adoption, these systems face several significant challenges, particularly the cold-start problem, data sparsity, pure cold-start, and the need for effective first impressions.
This book presents a concise overview of recommendation systems and investigates common problems.
By analysing these issues and presenting potential approaches, this book aims to contribute to the understanding of how recommendation systems can be improved to offer more precise recommendations from the outset.
