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Analogical modeling (AM) is a formal theory of exemplar based analogical reasoning, proposed by Royal Skousen, professor of Linguistics and English language at Brigham Young University in Provo, Utah. It is applicable to language modeling and other categorization tasks. Analogical modeling is related to connectionism and nearest neighbor approaches, in that it is data-based rather than abstraction-based; but it is distinguished by its ability to cope with imperfect datasets (such as caused by simulated short term memory limits) and to base predictions on all relevant segments of the dataset, whether near or far. In language modeling, AM has successfully predicted empirically valid forms for which no theoretical explanation was known (see the discussion of Finnish morphology in Skousen et a

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rdfs:label	Analogical modeling (en)
rdfs:comment	Analogical modeling (AM) is a formal theory of exemplar based analogical reasoning, proposed by Royal Skousen, professor of Linguistics and English language at Brigham Young University in Provo, Utah. It is applicable to language modeling and other categorization tasks. Analogical modeling is related to connectionism and nearest neighbor approaches, in that it is data-based rather than abstraction-based; but it is distinguished by its ability to cope with imperfect datasets (such as caused by simulated short term memory limits) and to base predictions on all relevant segments of the dataset, whether near or far. In language modeling, AM has successfully predicted empirically valid forms for which no theoretical explanation was known (see the discussion of Finnish morphology in Skousen et a (en)
differentFrom	Analogical model
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dcterms:subject	Classification algorithms Computational linguistics Analogy
Wikipage page ID	5481056 (xsd:integer)
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Link from a Wikipage to another Wikipage	Provo, Utah Royal Skousen Brigham Young University Instance-based learning Quantum computing Classification algorithms Computational Linguistics General-purpose modeling Orthography Morphology (linguistics) Connectionism Phonology Ferdinand de Saussure Noam Chomsky Computational linguistics Analogy K-nearest neighbor algorithm Syntax Nearest neighbor (pattern recognition) Exemplar theory Inconsistent
Link from a Wikipage to an external page	http://acl.ldc.upenn.edu/J/J91/J91-2010.pdf http://humanities.byu.edu/am https://web.archive.org/web/20030802024553/http:/acl.ldc.upenn.edu/J/J91/J91-2010.pdf http://humanities.byu.edu/am/bls_paper3.pdf https://archive.org/details/analogicalmodeli0000skou/page/ http://linguistlist.org/issues/14/14-110.html
sameAs	Analogical modeling Analogical modeling Analogical modeling Analogical modeling
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has abstract	Analogical modeling (AM) is a formal theory of exemplar based analogical reasoning, proposed by Royal Skousen, professor of Linguistics and English language at Brigham Young University in Provo, Utah. It is applicable to language modeling and other categorization tasks. Analogical modeling is related to connectionism and nearest neighbor approaches, in that it is data-based rather than abstraction-based; but it is distinguished by its ability to cope with imperfect datasets (such as caused by simulated short term memory limits) and to base predictions on all relevant segments of the dataset, whether near or far. In language modeling, AM has successfully predicted empirically valid forms for which no theoretical explanation was known (see the discussion of Finnish morphology in Skousen et al. 2002). (en)
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is Link from a Wikipage to another Wikipage of	Royal Skousen Scientific modelling Instance-based learning Analogical Modeling Lattice (order) The Master Algorithm Outline of machine learning
is Wikipage redirect of	Analogical Modeling
is foaf:primaryTopic of	wikipedia-en:Analogical_modeling

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