Advanced learning techniques for NLP

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F07%3A00041849" target="_blank" >RIV/00216224:14330/07:00041849 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

čeština

Název v původním jazyce

Advanced learning techniques for NLP

Popis výsledku v původním jazyce

Inductive logic programing (ILP) aims at learning first-order predicate formula from positive and maybe negative examples. This learning technique is not limited to single-table data (like most of other learning method) and is especially suitable for data of complex structure. ILP has been successful in part-of-speech tagging (English, Swedish, Spanish, Czech), error detection in a morphologically tagged Czech corpus, in text categorization and information extraction. The aim of the tutorial is to provide the participants with practical usage of ILP for several NLP tasks. Summary A brief overview of ILP ILP for Part-of-Speech Tagging. A case studies: POS tagging for English; Error detection in a Czech corpus ILP for Text filtering and Information Extraction A case studies: Filtering situations and action from news reports; Learning agent-target from biomedical texts First-order frequent patterns and association rules for NLP

Název v anglickém jazyce

Advanced learning techniques for NLP

Popis výsledku anglicky

Inductive logic programing (ILP) aims at learning first-order predicate formula from positive and maybe negative examples. This learning technique is not limited to single-table data (like most of other learning method) and is especially suitable for data of complex structure. ILP has been successful in part-of-speech tagging (English, Swedish, Spanish, Czech), error detection in a morphologically tagged Czech corpus, in text categorization and information extraction. The aim of the tutorial is to provide the participants with practical usage of ILP for several NLP tasks. Summary A brief overview of ILP ILP for Part-of-Speech Tagging. A case studies: POS tagging for English; Error detection in a Czech corpus ILP for Text filtering and Information Extraction A case studies: Filtering situations and action from news reports; Learning agent-target from biomedical texts First-order frequent patterns and association rules for NLP

Druh

O - Ostatní výsledky

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2007

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů