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MYŠKA,V. BURGET, R. BREZANY, P.
Originální název
Graph neural network for website element detection
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
graph neural network; deep learning; machine learning; node classification; mark-up languages
Autoři
MYŠKA,V.; BURGET, R.; BREZANY, P.
Vydáno
4. 7. 2019
Nakladatel
IEEE
Místo
Budapest, Hungary
ISBN
978-1-7281-1864-2
Kniha
42nd International Conference on Telecommunications and Signal Processing (TSP)
Strany od
216
Strany do
219
Strany počet
4
BibTex
@inproceedings{BUT157768, author="Vojtěch {Myška} and Radim {Burget} and Peter {Brezany}", title="Graph neural network for website element detection", booktitle="42nd International Conference on Telecommunications and Signal Processing (TSP)", year="2019", pages="216--219", publisher="IEEE", address="Budapest, Hungary", doi="10.1109/TSP.2019.8769036", isbn="978-1-7281-1864-2" }