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A semantic network, or frame network is a knowledge base that represents semantic relations between concepts in a network. This is often used as a form of knowledge representation . It is a directed or undirected graph consisting of vertices , which represent concepts , and edges , which represent semantic relations between concepts , [ 1 ...
Examples of knowledge representation formalisms include vocabularies, thesaurus, semantic networks, axiom systems, frames, rules, logic programs, and ontologies. Examples of automated reasoning engines include inference engines , theorem provers , model generators , and classifiers .
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 ...
A frame language is a technology used for knowledge representation in artificial intelligence. They are similar to class hierarchies in object-oriented languages although their fundamental design goals are different. Frames are focused on explicit and intuitive representation of knowledge whereas objects focus on encapsulation and information ...
In representation learning, knowledge graph embedding (KGE), also called knowledge representation learning (KRL), or multi-relation learning, [1] is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning.
Individuals using a computer with appropriate software can represent concepts and the relationships between concepts in a node-relationship-node formalism. The process of thinking about the concepts and making associations between them has been called "off-loading" by Ray McAleese. [1] The concept map is a form of a semantic network or
Semantic analysis (knowledge representation) Semantic data model; Semantic interoperability; Semantic knowledge management; Semantic network; Semantic parameterization;
The use of words to refer to concepts (the meanings of the words used) is very sensitive to the context and the purpose of any use for many human-readable terms. The use of ontologies in supporting semantic interoperability is to provide a fixed set of concepts whose meanings and relations are stable and can be agreed to by users.