What is a knowledge graph and where is it applied?

A knowledge graph is a data structure that represents information in the form of a graph, where nodes are entities (objects, concepts), and edges are relationships between them. Such a graph allows modeling complex interconnections and data context.

Applications of knowledge graphs:

• Search engines (e.g., Google Knowledge Graph) to improve relevance and provide extended information.
• Recommendation systems, where connections between users, products, and preferences are considered.
• Semantic web and data integration from various sources.
• Social network analysis, bioinformatics, and knowledge management in companies.

Knowledge graphs help systems better understand the meaning of data and make inferences based on relationships, which is important in artificial intelligence and machine learning tasks.