Reasoning Web. Explainable Artificial Intelligence: 15th International Summer School 2019, Bolzano, Italy, September 20–24, 2019, Tutorial Lectures

Description

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. Front Matter ....Pages i-xi Classical Algorithms for Reasoning and Explanation in Description Logics (Birte Glimm, Yevgeny Kazakov)....Pages 1-64 Explanation-Friendly Query Answering Under Uncertainty (Maria Vanina Martinez, Gerardo I. Simari)....Pages 65-103 Provenance in Databases: Principles and Applications (Pierre Senellart)....Pages 104-109 Knowledge Representation and Rule Mining in Entity-Centric Knowledge Bases (Fabian M. Suchanek, Jonathan Lajus, Armand Boschin, Gerhard Weikum)....Pages 110-152 Explaining Data with Formal Concept Analysis (Bernhard Ganter, Sebastian Rudolph, Gerd Stumme)....Pages 153-195 Logic-Based Learning of Answer Set Programs (Mark Law, Alessandra Russo, Krysia Broda)....Pages 196-231 Constraint Learning: An Appetizer (Stefano Teso)....Pages 232-249 A Modest Markov Automata Tutorial (Arnd Hartmanns, Holger Hermanns)....Pages 250-276 Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation (Extended Abstract) (Jörg Hoffmann, Daniele Magazzeni)....Pages 277-282 Back Matter ....Pages 283-283