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dc.contributor.authorKornai, András
dc.date.accessioned2022-12-13T12:40:53Z
dc.date.available2022-12-13T12:40:53Z
dc.date.issued2023
dc.identifierONIX_20221213_9789811956072_45
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/60191
dc.description.abstractThis open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.
dc.languageEnglish
dc.relation.ispartofseriesCognitive Technologies
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translationen_US
dc.subject.classificationthema EDItEUR::C Language and Linguistics::CF Linguistics::CFX Computational and corpus linguisticsen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligenceen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learningen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systemsen_US
dc.subject.classificationthema EDItEUR::D Biography, Literature and Literary studies::D Biography, Literature and Literary studies::DS Literature: history and criticismen_US
dc.subject.otherSemantics
dc.subject.otherNatural Language Processing
dc.subject.otherComputational Linguistics
dc.subject.otherArtificial Intelligence
dc.subject.otherexplainable AI
dc.subject.otherArtificial Neural Nets
dc.subject.otherlexical semantics
dc.subject.otherword vectors
dc.subject.otherembeddings
dc.subject.otherdynamic embeddings
dc.subject.otheralgebraic semantic
dc.subject.otherknowledge bases
dc.subject.othermachine learning
dc.titleVector Semantics
dc.typebook
oapen.identifier.doi10.1007/978-981-19-5607-2
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.relation.isFundedBya25a7f19-e1cd-4fa4-b6eb-9486269117a4
oapen.relation.isbn9789811956072
oapen.imprintSpringer
oapen.pages273
oapen.place.publicationSingapore
oapen.grant.number[...]


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