Graph neural network for website element detection

Autor: Vojtech Myska, Radim Burget, Brezany Peter
Rok vydání: 2019
Předmět:
Zdroj: TSP
DOI: 10.1109/tsp.2019.8769036
Popis: 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.
Databáze: OpenAIRE