E-Book, Englisch, 127 Seiten, eBook
Gupta / Jain Managing Event Information
1. Auflage 2022
ISBN: 978-3-031-01882-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 127 Seiten, eBook
Reihe: Synthesis Lectures on Data Management
ISBN: 978-3-031-01882-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
With the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning to generate information about events they observe and participate in. A significant fraction of this information contains multimedia data to share the experience with their audience. A systematic information modeling and management framework is necessary to capture this widely heterogeneous, schemaless, potentially humongous information produced by many different people. This book is an attempt to examine the modeling, storage, querying, and applications of such an event management system in a holistic manner. It uses a semantic-web style graph-based view of events, and shows how this event model, together with its query facility, can be used toward emerging applications like semi-automated storytelling. Table of Contents: Introduction / Event Data Models / Implementing an Event Data Model / Querying Events / Storytelling with Events / An Emerging Application / Conclusion
Amarnath Gupta is a Research Scientist at the San Diego Supercomputer Center of University of California San Diego. His current research interests are in the area of emerging information systems that include graph data management, semantic information integration for scientific applications, ontological information management, information management in social networks, and the impact of high-performance computing platforms for information systems problems. Before UCSD, he was at Virage, a multimedia information system company, and at the Indian Statistical Institute, Kolkata, India. He is a member of the ACM.
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Weitere Infos & Material
Introduction.- Event Data Models.- Implementing an Event Data Model.- Querying Events.- Storytelling with Events.- An Emerging Application.- Conclusion.