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.
%0 Book
%1 PanVetereEtAl2017
%C Cham
%D 2017
%E Pan, Jeff Z.
%E Vetere, Guido
%E Gomez-Perez, Jose Manuel
%E Wu, Honghan
%I Springer
%K 01624 103 springer book ai enterprise information management semantic web knowledge processing answer zzz.sw
%R 10.1007/978-3-319-45654-6
%T Exploiting Linked Data and Knowledge Graphs in Large Organisations
%X 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.
%@ 978-3-319-45652-2
@book{PanVetereEtAl2017,
abstract = {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.},
added-at = {2017-04-22T17:40:00.000+0200},
address = {Cham},
biburl = {https://www.bibsonomy.org/bibtex/259098315bbecd536bd55a7343b009c50/flint63},
doi = {10.1007/978-3-319-45654-6},
editor = {Pan, Jeff Z. and Vetere, Guido and Gomez-Perez, Jose Manuel and Wu, Honghan},
file = {SpringerLink:2017/PanVetereEtAl2017.pdf:PDF;Springer Product page:http\://www.springer.com/978-3-319-45652-2:URL;Amazon Search inside:http\://www.amazon.de/gp/reader/3319456520/:URL},
groups = {public},
interhash = {c518dc7e0f4169473973b2655b0e6115},
intrahash = {59098315bbecd536bd55a7343b009c50},
isbn = {978-3-319-45652-2},
keywords = {01624 103 springer book ai enterprise information management semantic web knowledge processing answer zzz.sw},
publisher = {Springer},
timestamp = {2017-07-13T17:08:32.000+0200},
title = {Exploiting Linked Data and Knowledge Graphs in Large Organisations},
username = {flint63},
year = 2017
}