How to Build a Real-Time Book Recommendation System on Amazon Books Dataset?

The blog post explores the creation of a real-time book recommendation system using the Amazon Books dataset, utilizing Memgraph's graph-based tools and algorithms for dynamic data processing. The process involves setting up Memgraph Cloud or a local instance, connecting to data streams, and using Memgraph Lab for querying and visualization. The system employs the PageRank algorithm to identify popular books and Python query modules to calculate average ratings and generate personalized recommendations by excluding books already rated by users. Additionally, the dynamic PageRank algorithm is introduced for efficient real-time updates in growing datasets. The blog provides a comprehensive guide for building recommendation engines with a focus on scalability and personalization, also encouraging further exploration of available datasets for similar projects.