Czech Dataset for Semantic Textual Similarity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952045" target="_blank" >RIV/49777513:23520/18:43952045 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-00794-2" target="_blank" >http://dx.doi.org/10.1007/978-3-030-00794-2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-00794-2" target="_blank" >10.1007/978-3-030-00794-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Czech Dataset for Semantic Textual Similarity

Popis výsledku v původním jazyce

Semantic textual similarity is the core shared task at the International Workshop on Semantic Evaluation (SemEval). It focuses on sentence meaning comparison. So far, most of the research has been devoted to English. In this paper we present first Czech dataset for semantic textual similarity. The dataset contains 1425 manually annotated pairs. Czech is highly inflected language and is considered challenging for many natural language processing tasks. The dataset is publicly available for the research community. In 2016 we participated at SemEval competition and our UWB system were ranked as second among 113 submitted systems in monolingual subtask and first among 26 systems in cross-lingual subtask. We adapt the UWB system for Czech (originally for English) and experiment with new Czech dataset. Our system achieves very promising results and can serve as a strong baseline for future research.

Název v anglickém jazyce

Czech Dataset for Semantic Textual Similarity

Popis výsledku anglicky

Semantic textual similarity is the core shared task at the International Workshop on Semantic Evaluation (SemEval). It focuses on sentence meaning comparison. So far, most of the research has been devoted to English. In this paper we present first Czech dataset for semantic textual similarity. The dataset contains 1425 manually annotated pairs. Czech is highly inflected language and is considered challenging for many natural language processing tasks. The dataset is publicly available for the research community. In 2016 we participated at SemEval competition and our UWB system were ranked as second among 113 submitted systems in monolingual subtask and first among 26 systems in cross-lingual subtask. We adapt the UWB system for Czech (originally for English) and experiment with new Czech dataset. Our system achieves very promising results and can serve as a strong baseline for future research.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

21st International Conference, TSD 2018, Brno, Czech Republic, September 11-14, 2018, Proceedings

ISBN

978-3-030-00793-5

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

9

Strana od-do

213-221

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Brno

Datum konání akce

11. 9. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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