Linked Data Storing, Querying, and Reasoning /

• Main Authors: Sakr, Sherif (Author, http://id.loc.gov/vocabulary/relators/aut), Wylot, Marcin (http://id.loc.gov/vocabulary/relators/aut), Mutharaju, Raghava (http://id.loc.gov/vocabulary/relators/aut), Le Phuoc, Danh (http://id.loc.gov/vocabulary/relators/aut), Fundulaki, Irini (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Subjects: Computers.; Artificial intelligence.; Information storage and retrieval.; Models and Principles.; Artificial Intelligence.; Information Storage and Retrieval.

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web...

Table of Contents:

• 1 Introduction
• 2 Fundamentals
• 3 Centralized RDF Query Processing
• 4 Distributed RDF Query Processing.- 5 Processing of RDF Stream Data
• 6 Distributed Reasoning of RDF Data
• 7 Benchmarking RDF Query Engines and Instance Matching Systems
• 8 Provenance Management for Linked Data
• 9 Conclusions and Outlook.