Exploiting linked data and knowledge graphs in large organisations / edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu.
نوع المادة : نصاللغة: الإنجليزية الناشر:Cham : Springer International Publishing : Imprint: Springer, 2017الطبعات:1st ed. 2017وصف:xviii, 266 pages : illustrations ; 24 cmنوع المحتوى:- text
- unmediated
- volume
- 9783319833392
- Q387 .E975 2017
نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
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كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | Q387 .E975 2017 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30020000207193 | ||
كتاب | UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | Q387 .E975 2017 (إستعراض الرف(يفتح أدناه)) | C.2 | المتاح | 30020000207192 |
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Part I Knowledge Graph Foundations and Architecture -- Part II Constructing, Understanding and Consuming Knowledge Graphs -- Part III Industrial Applications and Successful Stories.
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.