About: Exploiting Maching Learning for Automatic Semantic Feature Assignment

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	In this paper we experiment with supervised machine learning techniques for the task of assigning semantic categories to nouns in Czech. The experiments work with 16 semantic categories based on available manually annotated data. The paper compares two possible approaches - one based on the contextual information, the other based upon morphological properties - we are trying to automatically extract final segments of lemmas which might carry semantic information. The central problem of this research is finding the features for machine learning that produce better results for relatively small training data size. In this paper we experiment with supervised machine learning techniques for the task of assigning semantic categories to nouns in Czech. The experiments work with 16 semantic categories based on available manually annotated data. The paper compares two possible approaches - one based on the contextual information, the other based upon morphological properties - we are trying to automatically extract final segments of lemmas which might carry semantic information. The central problem of this research is finding the features for machine learning that produce better results for relatively small training data size. (en)
Title	Exploiting Maching Learning for Automatic Semantic Feature Assignment Exploiting Maching Learning for Automatic Semantic Feature Assignment (en)
skos:prefLabel	Exploiting Maching Learning for Automatic Semantic Feature Assignment Exploiting Maching Learning for Automatic Semantic Feature Assignment (en)
skos:notation	RIV/00216208:11320/13:10194625!RIV14-GA0-11320___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(GAP406/10/0875), S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Bílek, Karel Kuboň, Vladislav Klyueva, Natalia
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Karlova v Praze / Matematicko-fyzikální fakulta
http://linked.open...dnocenehoVysledku	74295
http://linked.open...ai/riv/idVysledku	RIV/00216208:11320/13:10194625
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	assignment; feature; semantic; automatic; learning; maching; exploiting (en)
http://linked.open.../riv/klicoveSlovo	automatic semantic assignment feature learning maching exploiting
http://linked.open...ontrolniKodProRIV	[F0DA3C24A2A8]
http://linked.open...v/mistoKonaniAkce	St. Pete Beach, Florida
http://linked.open...i/riv/mistoVydani	Palo Alto, California
http://linked.open...i/riv/nazevZdroje	Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Computational Linguistics: Explicit description of language and annotated data focused on Czech
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Kuboň, Vladislav Bílek, Karel Klyueva, Natalia
http://linked.open...vavai/riv/typAkce	CST - Celostátní
http://linked.open.../riv/zahajeniAkce	2013-05-22 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	AAAI Press
https://schema.org/isbn	978-1-57735-605-9
http://localhost/t...ganizacniJednotka	11320

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