Claudio Gutierrez – författare

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.

This book constitutes the thoroughly refereed post-conference proceedings of the joint International Workshops on Semantic Web, Ontologies and Databases, SWDB-ODBIS 2007, co-located with the 33rd International Conference on Very Large Data Bases, VLDB 2007, held in Vienna, Austria, in September 2007. The 7 revised full papers presented together with 1 invited paper were carefully selected from 11 submissions. Among the topics addressed are semantics-aware data models and query languages; ontology-based views, mapping, transformations, and query reformulation; and storing and indexing semantic Web data and schemas.

This book constitutes the thoroughly refereed post-conference proceedings of the joint International Workshops on Semantic Web, Ontologies and Databases, SWDB-ODBIS 2007, co-located with the 33rd International Conference on Very Large Data Bases, VLDB 2007, held in Vienna, Austria, in September 2007. The 7 revised full papers presented together with 1 invited paper were carefully selected from 11 submissions. Among the topics addressed are semantics-aware data models and query languages; ontology-based views, mapping, transformations, and query reformulation; and storing and indexing semantic Web data and schemas.

The Semantic Web is one of the major current endeavours of applied computer science. The Semantic Web aims at enriching the existing Web with meta-data and processing methods so as to provide Web-based systems with advanced (- called intelligent) capabilities, in particular with context-awarenessand decision support. TheadvancedcapabilitiesrequiredinmostSemanticWebapplicationscen- ios primarily call for reasoning. Reasoning capabilities are o?ered by Semantic Web languages that are currently being developed. Most of these languages, however,are developed mainly from functionality-centred perspectives (e.g., - tology reasoning or access validation) or application-centred perspectives (e.g., Web service retrieval and composition). A perspective centred on the reasoning techniques complementing the above-mentioned activities appears desirable for Semantic Web systems and applications. The Summer School is devoted to this perspective. The "ReasoningWeb" series of annual Summer Schools was started in 2005 on behalf of the work package "Education and Training (ET)" of the Network of Excellence REWERSE.This year's edition focused on the use of semantic technologies to enhance data access on the Web. For this reason, courses presented a range of techniques and formalisms which bridge semantic-based and data-intensive systems.

This book constitutes the refereed proceedings of the 5th International Conference on Web Reasoning and Rule Systems, RR 2011, held in Galway, Ireland in August 2011. The 13 revised full papers, 12 revised short papers presented together with 2 invited talks were carefully reviewed and selected from 36 submissions. The papers address all current topics in Semantic Web, interplay between classical reasoning approach with welll established web languages such as RDF and OWL, reasoning languages, querying and optimization and rules and ontologies.

This book constitutes the refereed proceedings of the 5th International Conference on Web Reasoning and Rule Systems, RR 2011, held in Galway, Ireland in August 2011. The 13 revised full papers, 12 revised short papers presented together with 2 invited talks were carefully reviewed and selected from 36 submissions. The papers address all current topics in Semantic Web, interplay between classical reasoning approach with welll established web languages such as RDF and OWL, reasoning languages, querying and optimization and rules and ontologies.