Subject
3 entries
Knowledge Graphs
Bookmarks
A Survey on Graph Representation Learning Methods
Khoshraftar and An (York University) provide a comprehensive survey of graph representation learning covering node embeddings, GNNs, and knowledge graph methods, with attention to both spectral and spatial approaches. It's the right starting point for anyone orienting to the GRL landscape — methodical coverage from DeepWalk through GAT.
Graph-Powered Machine Learning
Alessandro Negro's Manning book covers the intersection of graph theory and machine learning, from knowledge graphs and GNNs to fraud detection and recommendations using Neo4j. It's a practical end-to-end treatment that bridges graph databases and ML for practitioners.
An Introduction to Knowledge Graphs
Stanford AI Lab's introduction to knowledge graphs — what they are, how they're constructed, and where they're used. A solid conceptual overview covering entity linking, relation extraction, and the gap between structured and unstructured knowledge.