Detail publikace

Graph neural network for website element detection

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"
}