Discover AuraDB Free: Week 26 – Goodreads Books and Recommendations

This week, we're exploring book recommendation data as a graph using Goodreads. We create a Neo4j AuraDB Free instance and load the dataset into it. The dataset consists of books, authors, tags, ratings, and to-read lists. After processing the data, we can run exploratory queries on the database using Cypher, the query language for Neo4j. We also perform content-based recommendations by author and collaborative filtering by peers. These recommendations are generated based on the user's highly rated books from their peers who have similar rating behavior. The dataset provides a wealth of information about book genres, authors, tags, ratings, and user preferences, making it an excellent source for building a personalized book recommendation system.