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Big Data Analytics electronic resource Third International Conference, BDA 2014, New Delhi, India, December 20-23, 2014. Proceedings / edited by Srinath Srinivasa, Sameep Mehta.

Contributor(s): Srinivasa, Srinath [editor.] | Mehta, Sameep [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer SciencePublication details: Cham : Springer International Publishing : Imprint: Springer, 2014Description: X, 197 p. 83 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319138206Subject(s): Computer Science | Computer software | Database management | Data mining | Information storage and retrieval systems | Computer Science | Data Mining and Knowledge Discovery | Database Management | Information Storage and Retrieval | Algorithm Analysis and Problem ComplexityDDC classification: 006.312 LOC classification: QA76.9.D343Online resources: Click here to access online
Contents:
Media analytics -- Geospatial big data -- Semantics and data models -- Search and retrieval -- Graphics and visualization -- Application-specific big data.
In: Springer eBooksSummary: This book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.
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Media analytics -- Geospatial big data -- Semantics and data models -- Search and retrieval -- Graphics and visualization -- Application-specific big data.

This book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.

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