%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 }