| 書目名稱 | Exploiting Linked Data and Knowledge Graphs in Large Organisations |
| 編輯 | Jeff Z. Pan,Guido Vetere,Honghan Wu |
| 視頻video | http://file.papertrans.cn/320/319378/319378.mp4 |
| 概述 | Addresses the topic of exploiting enterprise linked data with a focus on knowledge construction and accessibility within enterprises.Focuses on the key technologies for constructing, understanding and |
| 圖書封面 |  |
| 描述 | 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, |
| 出版日期 | Book 2017 |
| 關(guān)鍵詞 | Linked Open Data; Knowledge Graphs; Semantic Web Technologies; Knowledge Representation and Reasoning; Q |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-45654-6 |
| isbn_softcover | 978-3-319-83339-2 |
| isbn_ebook | 978-3-319-45654-6 |
| copyright | Springer International Publishing Switzerland 2017 |
|Archiver|手機(jī)版|小黑屋|
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