Knowledge Representation in AI | Semantic Networks





Knowledge Representation In  AI | Semantic Networks


There are mainly four ways of knowledge representation which are given as follows: Logical Representation. Semantic Network Representation. Frame Representation


1)LOGICAL REPRESENTATION 


Logical representation is a language with some concrete rules which deals with propositions and has no ambiguity in representation. Logical representation means drawing a conclusion based on various conditions.. Each sentence can be translated into logics using syntax and semantics.


2)SEMANTIC NETWORK REPRESENTATION

Network representation learning aims to embed the vertexes in a network into low-dimensional dense representations, in which similar vertices in the network should have “close” representations (usually measured by cosine similarity or Euclidean distance of their representations).



3)FRAME   REPRESENTATION



Frames are an artificial intelligence data structure used to divide knowledge into substructures by representing "stereotyped situations". They were proposed by Marvin Minsky in his 1974 article "A Framework for Representing Knowledge"








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 TAGS:


FRAME PRESENTATION 
SEMANTICS  

 REASONING REPRESENTATION 



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