User:Phlsph7/Knowledge - representation & management

Knowledge representation
Knowledge representation is the field of inquiry within artificial intelligence that studies how computer systems can efficiently represent information. It investigates how different data structures and interpretative procedures can be combined to achieve this goal and which formal languages can be used to express knowledge items. Some efforts in this field are directed at developing general general languages and systems that can be employed in a great variety of domains while others focus on an optimized representation method within one specific domain. Knowledge representation is closely linked to automatic reasoning because the purpose of knowledge represntation formalisms is usually to construct a knowledge base from which inferences are drawn.

Influential knowledge base formalisms include logic-based systems, rule-based systems, Semantic networks, and frames. Logic-based systems rely on formal languages employed in logic to represent knowledge. They include devices like individual terms, predicates, and quantifiers. For rule-based systems, each unit of information is expressed using a conditional production rule of the form "if A then B". Semantic nets model knowledge as a graph consisting of vertices to represent facts or concepts and edges to represent the relations between them. Frames provide complex taxonomies to group items into classes, subclasses, and instances.

Knowledge management
Knowledge management is the process of creating, gathering, storing, and sharing knowledge. It involves the management of information assets that can take the form of documents, databases, policies, and procedures. It is of particular interest in the field of business and organizational development, as it directly impacts decision-making and strategic planning. Knowledge management efforts are often employed to increase operational efficiency in attempts to gain a competitive advantage.

Key processes in the field of knowledge management are knowledge creation, knowledge storage, knowledge sharing, and knowledge application. Knowledge creation is the frist step and involves the production of new information. The newly acquired knowledge has to be reliably stored to not become lost or forgotten. This can happen through different means, including books, audio recordings, film, and digital databases. Secure storage facilitates the the step of knowledge sharing, which involves transmitting the information from one person to another. For the knowledge to be beneficial, it has to be put into practice. This means that its insights should be used to either improve existing methods or implement new ones.