How Data Scientists Use Knowledge Graphs for Recommendation Systems

What this episode covers

On this episode of The Data Science Podcast, Lucas and Luna explore how knowledge graphs are transforming recommendation systems beyond traditional collaborative filtering. They dive into a real-world case from a major e-commerce platform that improved cross-category discovery by 22 percent using graph-based embeddings. The conversation covers the trade-offs between graph neural networks and embedding-based methods, the challenge of cold-start items, and why encoding user intent as relational paths matters more than ever. If you've ever wondered why your streaming service suggests a documentary about fungi after you watched a true crime series, this episode explains the graph structure behind that leap. #KnowledgeGraphs #RecommendationSystems #GraphNeuralNetworks #Embeddings #AI #MachineLearning #DataScience #Ecommerce #ColdStart #UserIntent #GraphBasedML #Technology #FexingoBusiness #BusinessPodcast #DataSciencePodcast #GraphAlgorithms #Personalization #GraphEmbeddings Keep every episode free: buymeacoffee.com/fexingo

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