• Facets (new session)
• Description
• Metadata
• Settings
  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: Pentti Kanerva     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : yago:Whole100003553, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)

Type: Thingyago:WikicatAmericanNeuroscientistsyago:WikicatLivingPeopleyago:Biologist109855630yago:CausalAgent100007347yago:LivingThing100004258yago:Neurobiologist110353928yago:Neuroscientist110354580yago:Object100002684yago:Organism100004475yago:Person100007846yago:PhysicalEntity100001930yago:YagoLegalActoryago:YagoLegalActorGeotelevision stationyago:Scientist110560637yago:Whole100003553 New Facet based on Instances of this Class

Pentti Kanerva is a research affiliate at the Redwood Neuroscience Institute, and is the originator of the sparse distributed memory model. He is responsible for relating the properties of long-term memory to mathematical properties of high-dimensional spaces and compares artificial neural-net associative memory to conventional computer random-access memory and to the neurons in the brain. This theory has been applied to design and implement the Random indexing approach to learning semantic relations from linguistic data.