Knowledge Graph
A structured network of entities and relationships that allows machines to understand how things connect, who relates to what, and what belongs to which category.
Also known as: knowledge graph dataset, entity graph, semantic graph
A knowledge graph is a data structure that represents information as a network of entities (nodes) and relationships (edges). Entities can be people, places, organizations, products, concepts, or events. Relationships describe how entities are connected: 'is a type of', 'is located in', 'is part of', 'was founded by', and so on.
Knowledge graphs give machines a structured way to understand the world beyond keyword matching. When an AI system can traverse a knowledge graph, it can answer relational questions, infer facts, and navigate from one entity to related entities. This is what powers many of the 'understanding' capabilities in modern search engines and AI assistants.
For businesses, publishing knowledge graph datasets about their entities, their products, and their domain makes it easier for AI systems to accurately understand and represent them.
Knowledge graphs give machines a structured way to understand the world beyond keyword matching. When an AI system can traverse a knowledge graph, it can answer relational questions, infer facts, and navigate from one entity to related entities. This is what powers many of the 'understanding' capabilities in modern search engines and AI assistants.
For businesses, publishing knowledge graph datasets about their entities, their products, and their domain makes it easier for AI systems to accurately understand and represent them.