Reasoning Web. Explainable Artificial Intelligence

15th International Summer School 2019, Bolzano, Italy, September 20–24, 2019, Tutorial Lectures

  • Markus Krötzsch
  • Daria Stepanova

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11810)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 11810)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Maria Vanina Martinez, Gerardo I. Simari
    Pages 65-103
  3. Fabian M. Suchanek, Jonathan Lajus, Armand Boschin, Gerhard Weikum
    Pages 110-152
  4. Bernhard Ganter, Sebastian Rudolph, Gerd Stumme
    Pages 153-195
  5. Mark Law, Alessandra Russo, Krysia Broda
    Pages 196-231
  6. Stefano Teso
    Pages 232-249
  7. Arnd Hartmanns, Holger Hermanns
    Pages 250-276
  8. Back Matter
    Pages 283-283

About this book


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.


international summer school semantic Web knowledge graphs rule-based reasoning data uncertainty scalability learning machine learning data management reasoning web semantics databases ontologies knowledge-based system World Wide Web

Editors and affiliations

  1. 1.Technische Universität DresdenDresdenGermany
  2. 2.Bosch Center for Artificial IntelligenceRenningenGermany

Bibliographic information

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