Knowledge representation is a term from the fields of Artificial Intelligence, Digital Transformation, and Big Data and Smart Data. It describes how knowledge \u2013 that is, information and experience \u2013 is stored in such a way that computers can work with it.<\/p>\n
For example, if an artificial intelligence is to support medical diagnoses, it must understand how different symptoms and diseases are related. These relationships are captured through knowledge representation, for instance, as lists, networks, or tables, which show how terms and facts fit together. The machine uses this \u201eknowledge\u201c to find answers or make decisions.<\/p>\n
A clear example: Imagine teaching a computer how to classify animals. Knowledge representation gathers characteristics such as \u201ehas feathers\u201c or \u201ecan fly\u201c. This allows the system, for instance, to recognise that a sparrow is a bird, as both attributes match.<\/p>\n
Knowledge representation is therefore a foundation for machines to not only store information but also to \u201eunderstand\u201c and apply it. This subject is becoming increasingly important, especially in the age of artificial intelligence and data-driven processes.<\/p>","protected":false},"excerpt":{"rendered":"