Exploiting Linked Data and Knowledge Graphs in Large Organisations

Author:   Jeff Z. Pan ,  Guido Vetere ,  Jose Manuel Gomez-Perez ,  Honghan Wu
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2017
ISBN:  

9783319456522


Pages:   266
Publication Date:   09 February 2017
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Exploiting Linked Data and Knowledge Graphs in Large Organisations


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Author:   Jeff Z. Pan ,  Guido Vetere ,  Jose Manuel Gomez-Perez ,  Honghan Wu
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2017
Dimensions:   Width: 15.50cm , Height: 1.80cm , Length: 23.50cm
Weight:   5.502kg
ISBN:  

9783319456522


ISBN 10:   3319456520
Pages:   266
Publication Date:   09 February 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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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