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Managing event information : modeling, retrieval, and applications /

By: Gupta, Amarnath.
Contributor(s): Jain, Ramesh 1949-.
Material type: materialTypeLabelBookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on data management: # 19.Publisher: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, c2011Description: 1 electronic text (x, 127 p.) : ill., digital file.ISBN: 9781608453528 (electronic bk.).Subject(s): Event processing (Computer science) | Multimedia systems | Social media -- Mathematical models | Digital storytelling -- Mathematical models | Citizen journalism -- Mathematical models | event management system | graph data | graph query language | storytelling | event queriesDDC classification: 006.7 Online resources: Abstract with links to resource Also available in print.
Contents:
Preface -- Acknowledgments --
1. Introduction -- 1.1 A running example, the setting -- 1.2 Events and information systems -- 1.2.1 Active databases -- 1.2.2 Complex event processing -- 1.2.3 Event-oriented spatiotemporal databases -- 1.3 Events and sensor networks -- 1.4 Events and multimedia information systems -- 1.4.1 Events from video and audio analysis -- 1.4.2 Events in surveillance systems -- 1.4.3 Multimedia and semantic events --
2. Event data models -- 2.1 Modeling events on temporal databases -- 2.1.1 Example: Newsan's politician database -- 2.1.2 Events as value changes -- 2.2 Modeling events with conceptual temporal models -- 2.3 E*, a graph-based event model using RDF and ontologies -- 2.3.1 Example: Newsan covers a rally that turned violent -- 2.3.2 Modeling time in E* -- 2.3.3 Modeling location in E* -- 2.3.4 Modeling granularity of perdurants -- 2.3.5 The semantics of the subevent-of relationship -- 2.3.6 The semantics of collective events -- 2.3.7 Modeling constructs for events --
3. Implementing an event data model -- 3.1 An extended entity relationship model for structured events -- 3.2 A pattern-based approach to structured events -- 3.3 A hybrid approach for structured and semi-structured events -- 3.4 An implementation scheme for E* -- 3.4.1 Declaring E* events with E*ML -- 3.4.2 Toward a physical model for E* events --
4. Querying events -- 4.1 Characterizing event queries -- 4.2 A query processing architecture -- 4.3 The semantic catalog -- 4.4 An algebraic framework for E*ML query processing --
5. Storytelling with events -- 5.1 Formulating the problem -- 5.2 A story request language -- 5.3 Algorithms for storytelling --
6. An emerging application -- 7. Conclusion -- A. An RDF primer -- Bibliography -- Authors' biographies.
Abstract: With the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning generate information about events they observe and participate in. A significant fraction of this information contain 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.
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E books E books PK Kelkar Library, IIT Kanpur
Available EBKE369
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Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 115-126).

Preface -- Acknowledgments --

1. Introduction -- 1.1 A running example, the setting -- 1.2 Events and information systems -- 1.2.1 Active databases -- 1.2.2 Complex event processing -- 1.2.3 Event-oriented spatiotemporal databases -- 1.3 Events and sensor networks -- 1.4 Events and multimedia information systems -- 1.4.1 Events from video and audio analysis -- 1.4.2 Events in surveillance systems -- 1.4.3 Multimedia and semantic events --

2. Event data models -- 2.1 Modeling events on temporal databases -- 2.1.1 Example: Newsan's politician database -- 2.1.2 Events as value changes -- 2.2 Modeling events with conceptual temporal models -- 2.3 E*, a graph-based event model using RDF and ontologies -- 2.3.1 Example: Newsan covers a rally that turned violent -- 2.3.2 Modeling time in E* -- 2.3.3 Modeling location in E* -- 2.3.4 Modeling granularity of perdurants -- 2.3.5 The semantics of the subevent-of relationship -- 2.3.6 The semantics of collective events -- 2.3.7 Modeling constructs for events --

3. Implementing an event data model -- 3.1 An extended entity relationship model for structured events -- 3.2 A pattern-based approach to structured events -- 3.3 A hybrid approach for structured and semi-structured events -- 3.4 An implementation scheme for E* -- 3.4.1 Declaring E* events with E*ML -- 3.4.2 Toward a physical model for E* events --

4. Querying events -- 4.1 Characterizing event queries -- 4.2 A query processing architecture -- 4.3 The semantic catalog -- 4.4 An algebraic framework for E*ML query processing --

5. Storytelling with events -- 5.1 Formulating the problem -- 5.2 A story request language -- 5.3 Algorithms for storytelling --

6. An emerging application -- 7. Conclusion -- A. An RDF primer -- Bibliography -- Authors' biographies.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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With the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning generate information about events they observe and participate in. A significant fraction of this information contain 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.

Also available in print.

Title from PDF t.p. (viewed on August 14, 2011).

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