Reasoning Web. Learning, Uncertainty, Streaming, and Scalability

Claudia D'Amato

ISBN 10: 303000337X / ISBN 13: 9783030003371

Published by Springer, Springer Aug 2018, 2018

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 252 pp. Englisch.

Seller Inventory # 9783030003371

Bibliographic Details

• Title: Reasoning Web. Learning, Uncertainty, Streaming, and Scalability
• Publisher: Springer, Springer Aug 2018
• Publication Date: 2018
• Language: English
• ISBN 10: 303000337X
• ISBN 13: 9783030003371
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 14D millimeters 235 millimeters width by 155 millimeters height by 14 millimeters depth
• Weight: 388 grams

About this title

Synopsis

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.

About the Author

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.