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This book constitutes the refereed proceedings of the 7th International Conference on Knowledge Engineering and the Semantic Web, KESW 2016, held in Prague, Czech Republic, in September 2016. The 17 revised full papers presented together with 9 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on ontologies; information and knowledge extraction; data management; applications.

Computer science. --- Database management. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Text processing (Computer science). --- Computer Science. --- Information Storage and Retrieval. --- Artificial Intelligence (incl. Robotics). --- Database Management. --- Document Preparation and Text Processing. --- Data Mining and Knowledge Discovery. --- Processing, Text (Computer science) --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Informatics --- Information storage and retrieva. --- Natural language processing (Computer science). --- Artificial Intelligence. --- Natural Language Processing (NLP). --- Database searching --- Electronic data processing --- NLP (Computer science) --- Artificial intelligence --- Human-computer interaction --- Semantic computing --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Software engineering

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Electrical & Computer Engineering --- Engineering & Applied Sciences --- Telecommunications --- Information Technology --- Computer Science (Hardware & Networks)

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Information retrieval --- Mathematical logic --- Programming --- Computer architecture. Operating systems --- Information systems --- Computer. Automation --- NLP (neurolinguïstisch programmeren) --- applicatiebeheer --- apps --- informatiesystemen --- database management --- wiskunde --- architectuur (informatica) --- informatietheorie

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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.

Internet programming. --- Ontology. --- Web Development. --- Graphic methods --- Information visualization. --- Graphic methods. --- Semantic computing. --- Conceptual structures (Information theory) --- Computer programs.