Distributional Learning of Simple Context-Free Tree Grammars
Identifieur interne : 001680 ( Istex/Curation ); précédent : 001679; suivant : 001681Distributional Learning of Simple Context-Free Tree Grammars
Auteurs : Anna Kasprzik [Allemagne] ; Ryo Yoshinaka [Japon]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.
Url:
DOI: 10.1007/978-3-642-24412-4_31
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<record><TEI wicri:istexFullTextTei="biblStruct:series"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Distributional Learning of Simple Context-Free Tree Grammars</title><author><name sortKey="Kasprzik, Anna" sort="Kasprzik, Anna" uniqKey="Kasprzik A" first="Anna" last="Kasprzik">Anna Kasprzik</name><affiliation><mods:affiliation>FB IV Informatik, University of Trier, 54286, Trier</mods:affiliation><wicri:noCountry code="subField">Trier</wicri:noCountry></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: kasprzik@informatik.uni-trier.de</mods:affiliation><country wicri:rule="url">Allemagne</country></affiliation></author><author><name sortKey="Yoshinaka, Ryo" sort="Yoshinaka, Ryo" uniqKey="Yoshinaka R" first="Ryo" last="Yoshinaka">Ryo Yoshinaka</name><affiliation wicri:level="1"><mods:affiliation>ERATO MINATO Project, Japan Science and Technology Agency, Japan</mods:affiliation><country xml:lang="fr">Japon</country><wicri:regionArea>ERATO MINATO Project, Japan Science and Technology Agency</wicri:regionArea></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: ry@ist.hokudai.ac.jp</mods:affiliation><country wicri:rule="url">Japon</country></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:B0186252445537B2343714CEAE46FF0F4725DEB8</idno><date when="2011" year="2011">2011</date><idno type="doi">10.1007/978-3-642-24412-4_31</idno><idno type="url">https://api.istex.fr/document/B0186252445537B2343714CEAE46FF0F4725DEB8/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">001796</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">001796</idno><idno type="wicri:Area/Istex/Curation">001680</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Distributional Learning of Simple Context-Free Tree Grammars</title><author><name sortKey="Kasprzik, Anna" sort="Kasprzik, Anna" uniqKey="Kasprzik A" first="Anna" last="Kasprzik">Anna Kasprzik</name><affiliation><mods:affiliation>FB IV Informatik, University of Trier, 54286, Trier</mods:affiliation></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: kasprzik@informatik.uni-trier.de</mods:affiliation><country wicri:rule="url">Allemagne</country></affiliation></author><author><name sortKey="Yoshinaka, Ryo" sort="Yoshinaka, Ryo" uniqKey="Yoshinaka R" first="Ryo" last="Yoshinaka">Ryo Yoshinaka</name><affiliation wicri:level="1"><mods:affiliation>ERATO MINATO Project, Japan Science and Technology Agency, Japan</mods:affiliation><country xml:lang="fr">Japon</country><wicri:regionArea>ERATO MINATO Project, Japan Science and Technology Agency</wicri:regionArea></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: ry@ist.hokudai.ac.jp</mods:affiliation><country wicri:rule="url">Japon</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2011</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">B0186252445537B2343714CEAE46FF0F4725DEB8</idno><idno type="DOI">10.1007/978-3-642-24412-4_31</idno><idno type="ChapterID">31</idno><idno type="ChapterID">Chap31</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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