Big Data Analytics and Knowledge Discovery [electronic resource] : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings / edited by Sanjay Madria, Takahiro Hara.
Contributor(s): Madria, Sanjay [editor.] | Hara, Takahiro [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Computer Science: 9263Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015.Description: XIII, 418 p. 116 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319227290.Subject(s): Computer science | Database management | Data mining | Information storage and retrieval | Application software | Computer Science | Database Management | Data Mining and Knowledge Discovery | Computer Appl. in Administrative Data Processing | Information Storage and Retrieval | Information Systems Applications (incl. Internet)Additional physical formats: Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online In: Springer eBooksSummary: This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.No physical items for this record
This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.
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