Explanation
Imagine a spider's web, but instead of catching insects, it captures knowledge. That’s essentially what a knowledge graph is. It's a way of organising information by connecting related concepts, entities, and facts in a network.
Each 'node' in the graph represents a concept or entity (like a person, place, or thing), and the 'edges' represent the relationships between them. Instead of scattered data points, you get a rich, interconnected web of information.
Knowledge graphs allow computers to understand the context and relationships between different pieces of information. They are also designed to mimic how the human brain stores and retrieves information, making it easier to find relevant insights and make informed decisions.
Knowledge graphs are powerful because they provide a framework for linking disparate data sources and uncovering hidden connections. They allow us to go beyond simple searches and explore the complex relationships between things.
Examples
Consumer Example
Think about how Netflix recommends films you might enjoy. It doesn't just look at films you've previously watched; it considers the actors, directors, genre, and other related information.
All of this information is stored in a knowledge graph that allows Netflix to understand the connections between different films and make more informed recommendations. It's like having a film buff friend who knows exactly what you'll like.
Business Example
Imagine a pharmaceutical company using a knowledge graph to accelerate drug discovery. The graph connects information about diseases, genes, drugs, and clinical trials, allowing researchers to identify potential drug candidates and predict their effectiveness.
By visualising the relationships between these entities, researchers can discover new insights and develop targeted therapies more efficiently. It's like having a super-powered research assistant that can sift through vast amounts of data and identify promising leads.