Reasoning Web. Explainable Artificial Intelligence
Produktnummer:
185e76a1d9455f413aa392c86469914528
Themengebiete: | data management data uncertainty international summer school knowledge graphs learning machine learning reasoning web rule-based reasoning scalability semantic Web |
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Veröffentlichungsdatum: | 18.09.2019 |
EAN: | 9783030314224 |
Sprache: | Englisch |
Seitenzahl: | 283 |
Produktart: | Kartoniert / Broschiert |
Herausgeber: | Krötzsch, Markus Stepanova, Daria |
Verlag: | Springer International Publishing |
Untertitel: | 15th International Summer School 2019, Bolzano, Italy, September 20–24, 2019, Tutorial Lectures |
Produktinformationen "Reasoning Web. Explainable Artificial Intelligence"
This volume contains lecture notes of the 15th Reasoning Web Summer School (RW 2019), held in Bolzano, Italy, in September 2019. 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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