A Siamese neural network for learning semantically-informed sentence embeddings
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AX2I5KRSP" target="_blank" >RIV/00216208:11320/23:X2I5KRSP - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0957417422021212" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0957417422021212</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.eswa.2022.119103" target="_blank" >10.1016/j.eswa.2022.119103</a>
Alternative languages
Result language
angličtina
Original language name
A Siamese neural network for learning semantically-informed sentence embeddings
Original language description
"In this paper, we present a semantic parsing model based on neural networks to obtain semantic representation of a given sentence. We utilise semantic representation of each sentence to generate semantically informed sentence embeddings for extrinsic evaluation of the proposed semantic parser, in particular for the semantic textual similarity task."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
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
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Expert Systems with Applications"
ISSN
1873-6793
e-ISSN
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Volume of the periodical
214
Issue of the periodical within the volume
2023
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
1-12
UT code for WoS article
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EID of the result in the Scopus database
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