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Knowledge management products adopted the term "knowledge-base" to describe their repositories but the meaning had a big difference. In the case of previous knowledge-based systems, the knowledge was primarily for the use of an automated system, to reason about and draw conclusions about the world.
The knowledge base contains domain-specific facts and rules [1] about a problem domain (rather than knowledge implicitly embedded in procedural code, as in a conventional computer program). In addition, the knowledge may be structured by means of a subsumption ontology , frames , conceptual graph , or logical assertions.
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...
Knowledge management (KM) is the set of procedures for producing, disseminating, utilizing, and overseeing an organization's knowledge and data.It alludes to a multidisciplinary strategy that maximizes knowledge utilization to accomplish organizational goals.
One of the most well known of these early Lisp knowledge-base tools was the Knowledge Engineering Environment (KEE) from Intellicorp. KEE provided a full Frame language with multiple inheritance, slots, triggers, default values, and a rule engine that supported backward and forward chaining.
Knowledge-based decision making model [1] Knowledge-Based Decision-Making (KBDM) in management is a decision-making process [2] that uses predetermined criteria to measure and ensure the optimal outcome for a specific topic. KBDM is used to make decisions by establishing a thought process and reasoning behind a decision. [3]
Notable knowledge management tools include: Bloomfire – Knowledge sharing software with AI; Collective Knowledge – An open source, portable and command line framework for knowledge management; Confluence – Wiki-based knowledge management software that is part of Atlassian's suite; eGain – Knowledge management and AI software
Knowledge representation goes hand in hand with automated reasoning because one of the main purposes of explicitly representing knowledge is to be able to reason about that knowledge, to make inferences, assert new knowledge, etc. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system.