Graph neural network for website element detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU132722" target="_blank" >RIV/00216305:26220/19:PU132722 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TSP.2019.8769036" target="_blank" >http://dx.doi.org/10.1109/TSP.2019.8769036</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2019.8769036" target="_blank" >10.1109/TSP.2019.8769036</a>

Result language
angličtina
Original language name
Graph neural network for website element detection
Original language description
Websites are a mixture of structured HTML tags, unstructured natural language and styling, which gives a wide range of possibilities how a website can look like. The paper introduces a website node detector based on the so-called graph neural networks - a new kind of neural networks, which are not working just with tensors like traditional neural networks do, but operates with graphs (or tree structures - special variations of graphs). To assess the accuracy of the proposed methodology, a privately collected and labeled data set was created. Although the data set used for the experiment is relatively limited, results on this limited data set suggest, that this methodology may be a promising path for automatic content generation.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
42nd International Conference on Telecommunications and Signal Processing (TSP)
ISBN
978-1-7281-1864-2
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
216-219
Publisher name
IEEE
Place of publication
Budapest, Hungary
Event location
Budapest, Hungary
Event date
Jul 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000493442800047

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