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Książka Reasoning Web. Learning, Uncertainty, Streaming, and Scalability Claudia D'Amato

Reasoning Web. Learning, Uncertainty, Streaming, and Scalability

Autor: Claudia D'Amato, Martin Theobald
Język: Angielski
Oprawa: Miękka
Wydawca: Springer Nature Switzerland AG
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
214.72 zł
This volume contains lecture notes of the 14th Reasoning Web Summer School (RW 2018), held in Esch-s...

Informacje o książce

Autor
Claudia D'Amato, Martin Theobald
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2018
strony
237
EAN
9783030003371
ISBN
303000337X
Enbook ID
20085649
Wydawca
Springer Nature Switzerland AG
Waga
391
Wymiary
155 x 235 x 12

Pełny opis

This volume contains lecture notes of the 14th Reasoning Web Summer School (RW 2018), held in Esch-sur-Alzette, Luxembourg, in September 2018. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.

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