Exploiting Linked Data and Knowledge Graphs in Large Organisations [[electronic resource] /] / edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• Edizione: 1st ed. 2017.
• Descrizione fisica: 1 online resource (XVIII, 266 p. 59 illus., 44 illus. in color.)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Data mining; Application software; Management information systems; Artificial Intelligence; Data Mining and Knowledge Discovery; Information Systems Applications (incl. Internet); Business Information Systems
• Persona (resp. second.): PanJeff Z; VetereGuido; Gomez-PerezJose Manuel; WuHonghan
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Part I Knowledge Graph Foundations & Architecture -- Part II Constructing, Understanding and Consuming Knowledge Graphs -- Part III Industrial Applications and Successful Stories.
• Sommario/riassunto: This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and “standard” data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.
• Titolo autorizzato: Exploiting Linked Data and Knowledge Graphs in Large Organisations
• ISBN: 3-319-45654-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910163028403321
• Lo trovi qui: Univ. Federico II