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Machine Learning for Semantic Parsing in Review

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10318122" target="_blank" >RIV/00216208:11320/15:10318122 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Machine Learning for Semantic Parsing in Review

  • Original language description

    Spoken Language Understanding (SLU) and more specifically, semantic parsing is an indispensable task in each speech-enabled application. In this survey, we review the current research on SLU and semantic parsing with emphasis on machine learning techniques used for these tasks. Observing the current trends in semantic parsing, we conclude our discussion by suggesting some of the most promising future research trends.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/LK11221" target="_blank" >LK11221: Development of statistical methods for spoken dalogue systems</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 7rd Language and Technology Conference

  • ISBN

    978-83-932640-8-7

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    535-539

  • Publisher name

    Fundacja Uniwersytetu im. Adama Mickiewicza w Poznaniu

  • Place of publication

    Poznań, Poland

  • Event location

    Poznań, Poland

  • Event date

    Nov 27, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article