Evaluation Datasets for Cross-lingual Semantic Textual Similarity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43963751" target="_blank" >RIV/49777513:23520/21:43963751 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2021.ranlp-main.59.pdf" target="_blank" >https://aclanthology.org/2021.ranlp-main.59.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.26615/978-954-452-072-4_059" target="_blank" >10.26615/978-954-452-072-4_059</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation Datasets for Cross-lingual Semantic Textual Similarity
Original language description
Semantic textual similarity (STS) systems estimate the degree of the meaning similarity between two sentences. Cross-lingual STS systems estimate the degree of the meaning similarity between two sentences, each in a different language. State-of-the-art algorithms usually employ a strongly supervised, resource-rich approach difficult to use for poorly-resourced languages. However, any approach needs to have evaluation data to confirm the results. In order to simplify the evaluation process for poorly-resourced languages (in terms of STS evaluation datasets), we present new datasets for cross-lingual and monolingual STS for languages without this evaluation data. We also present the results of several state-of-the-art methods on these data which can be used as a baseline for further research. We believe that this article will not only extend the current STS research to other languages, but will also encourage competition on this new evaluation data.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF17_048%2F0007267" target="_blank" >EF17_048/0007267: Research and Development of Intelligent Components of Advanced Technologies for the Pilsen Metropolitan Area (InteCom)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Deep Learning for Natural Language Processing Methods and Applications
ISBN
978-954-452-072-4
ISSN
1313-8502
e-ISSN
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Number of pages
6
Pages from-to
524-529
Publisher name
INCOMA, Ltd.
Place of publication
Shoumen
Event location
Shoumen, Bulgaria
Event date
Sep 1, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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