Building a Recommendation System Using Memgraph

Memgraph's approach to building an objective recommendation system leverages the Cypher query language to focus on the inherent characteristics of products, rather than relying on traditional numerical ratings. This system uses a graph structure where nodes represent games and their attributes, while edges denote relationships with assigned relevance properties, allowing for nuanced recommendations. Unlike collaborative filtering, which predicts user interest based on ratings from other users, this method emphasizes the characteristics of games such as genre, developer, and publisher. By employing graph algorithms such as Breadth-First Search and Dijkstra’s algorithm, the system can efficiently identify paths and relationships between games or companies. The recommendation system's flexibility allows for expansion through more detailed data, alternative relevance systems, or descriptive reviews, thus offering a sophisticated method for generating recommendations in contexts like gaming platforms, exemplified by comparisons between games such as Stardew Valley and Forager.