Reasoning Web. Learning, Uncertainty, Streaming, and Scalability

1. Front Matter

   Pages I-XI

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2. Practical Normative Reasoning with Defeasible Deontic Logic

   • Guido Governatori

   Pages 1-25

3. Efficient and Convenient SPARQL+Text Search: A Quick Survey

   • Hannah Bast, Niklas Schnelle

   Pages 26-34

4. A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases

   • İsmail İlkan Ceylan, Thomas Lukasiewicz

   Pages 35-77

5. Cold-Start Knowledge Base Population Using Ontology-Based Information Extraction with Conditional Random Fields

   • Hendrik ter Horst, Matthias Hartung, Philipp Cimiano

   Pages 78-109

6. Machine Learning with and for Semantic Web Knowledge Graphs

   • Heiko Paulheim

   Pages 110-141

7. Rule Induction and Reasoning over Knowledge Graphs

   • Daria Stepanova, Mohamed H. Gad-Elrab, Vinh Thinh Ho

   Pages 142-172

8. Storing and Querying Semantic Data in the Cloud

   • Daniel Janke, Steffen Staab

   Pages 173-222

9. Engineering of Web Stream Processing Applications

   • Emanuele Della Valle, Riccardo Tommasini, Marco Balduini

   Pages 223-226

10. Reasoning at Scale (Tutorial)

    • Jacopo Urbani

    Pages 227-235

11. Back Matter

    Pages 237-237

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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 makeRDF 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

• University of Bari Aldo Moro, Bari, Italy

  Claudia d’Amato

• University of Luxembourg, Esch-sur-Alzette, Luxembourg

  Martin Theobald

Since December 2016, Claudia d'Amato is in tenure track for associate professorship in Computer Science at the University of Bari. She obtained the Italian Habilitation for the functions of Associate Professor for the Scientific Sector “01/B1 – Informatics” on January 29th, 2014, (Application: round 2012). Before she has been appointed as assistant professor at the University of Bari on January 2016 and I have been research fellow at the University of Bari since May 2007 to December 2015. 



Martin Theobald (born 1976) has been appointed as a Professor of Computer Science with a focus on “Big Data” by the Faculty of Science, Technology and Communication (FSTC) at the University of Luxembourg in February 2017. 

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