Scraping Data from Web Pages using SPARQL Queries

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU148340" target="_blank" >RIV/00216305:26230/23:PU148340 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-34444-2_21" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-34444-2_21</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Scraping Data from Web Pages using SPARQL Queries
Original language description
Despite the increasing use of semantic data, plain old HTML web pages often provide a unique interface for accessing data from many domains. To use this data in computer applications or to integrate it with other data sources, it must be extracted from the HTML code. Currently, this is typically done by single-purpose programs called scrapers. For each data source, specific scrapers must be created, which requires a thorough analysis of the source page's implementation in HTML. This makes writing and maintaining a set of scrapers a complex and time-consuming task. In this paper, we present an alternative approach that allows defining scrapers based on visual properties of the presented content instead of the HTML code structure. First, we render the source page and create an RDF graph that describes the visual properties of every piece of the displayed content. Next, we use SPARQL to query the model and extract the data. As we demonstrate with real-world examples, this approach allows us t
Czech name
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Czech description
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Type
O - Miscellaneous
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)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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