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Jeff Z. (Hrsg.) Pan

Exploiting Linked Data and Knowledge Graphs in Large Organisations

Ebook (PDF Format)

This book addresses the topic of exploiting enterprise-linked data with a particularfocus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and standarddata consuming technologies by analysing real-world use cases, and proposes theenterprise knowledge graph to fill such gaps.It provides concrete guidelines for effectively deploying linked-data graphs withinand across business organizations. It is divided into three parts, focusing on the keytechnologies for constructing, understanding and employing knowledge graphs.Part 1 introduces basic backgro… Mehr

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Produktdetails


Weitere Autoren: Wu, Honghan (Hrsg.) / Vetere, Guido (Hrsg.) / Gomez-Perez, Jose Manuel (Hrsg.)
  • ISBN: 978-3-319-45654-6
  • EAN: 9783319456546
  • Produktnummer: 22285513
  • Verlag: Springer
  • Sprache: Englisch
  • Erscheinungsjahr: 2017
  • Plattform: PDF
  • Masse: 8'041 KB

Über den Autor


About the Editors: Jeff Z. Pan is a Reader (Professor) at University of Aberdeen. He is the Chief Scientist of the EC Marie Curie K-Drive project and has edited many books/proceedings on Semantic Technologies and Linked Data. He is well known for his work on knowledge construction, reasoning and exploitation.  Guido Vetere leads the IBM Center for Advanced Studies Italy. He has led/worked in many research and development projects in KR, NLP and ontology. He also leads Senso Comune (www.sensocomune.it), a collaborative initiative for building an open KB of the Italian language. Jose Manuel Gomez-Perez is the Director R&D at Expert System Iberia (ESI). His expertise is on supporting users in creating, sharing, and accessing knowledge. He has a long experience in European R&D projects, privately-funded technology transfer activities and R&D projects. Honghan Wu is a data scientist in NIHR Maudsley Biomedical Research Centre at King's College London. His current research focus is on annotating, analysing and searching large scale healthcare data by utilising Knowledge Graph techniques.

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