NETL: A System for Representing and Using Real-World Knowledge
E474909
NETL: A System for Representing and Using Real-World Knowledge is an influential early work in artificial intelligence that introduces a network-based framework for encoding and reasoning about commonsense knowledge.
Statements (38)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence research work
ⓘ
book ⓘ knowledge representation system ⓘ |
| addresses |
efficient retrieval of knowledge
ⓘ
reasoning with incomplete information ⓘ representation of structured knowledge ⓘ |
| approach |
graph-structured representation of concepts
ⓘ
nodes and links to represent entities and relations ⓘ |
| contribution |
early network-based knowledge representation formalism
ⓘ
methods for representing real-world entities and relations ⓘ techniques for inference over semantic networks ⓘ |
| describes |
framework for encoding knowledge
ⓘ
framework for reasoning about knowledge ⓘ |
| field |
artificial intelligence
ⓘ
commonsense reasoning ⓘ knowledge representation ⓘ |
| focusesOn |
commonsense knowledge
ⓘ
real-world knowledge ⓘ |
| goal | enable machines to use real-world knowledge effectively ⓘ |
| hasAuthor | Scott E. Fahlman NERFINISHED ⓘ |
| hasShortName | NETL NERFINISHED ⓘ |
| influenced |
frame-based knowledge representation
ⓘ
later semantic network systems ⓘ subsequent AI knowledge bases ⓘ |
| influencedField |
commonsense reasoning research
ⓘ
knowledge representation research ⓘ |
| notableFor | being an influential early AI knowledge representation system ⓘ |
| relatedTo |
early expert systems
ⓘ
frames in AI ⓘ semantic networks in AI ⓘ |
| supports |
inference over linked concepts
ⓘ
reasoning about everyday situations ⓘ |
| topic |
encoding of default and typical knowledge
ⓘ
organization of large knowledge bases ⓘ representation of objects, properties, and relations ⓘ |
| typeOfSystem | symbolic AI system ⓘ |
| usesRepresentation |
network-based knowledge representation
ⓘ
semantic network ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.