Business Intelligence

4th European Summer School, eBISS 2014, Berlin, Germany, July 6-11, 2014, Tutorial Lectures
Buch | Softcover
IX, 149 Seiten
2015 | 2015
Springer International Publishing (Verlag)
978-3-319-17550-8 (ISBN)

Lese- und Medienproben

Business Intelligence -
42,80 inkl. MwSt

This book constitutes the tutorial lectures of the 4th European Business Intelligence Summer School, eBISS 2014, held in Berlin, Germany, in July 2014.

The tutorials presented here in an extended and refined format were given by renowned experts and cover topics including requirements engineering for decision-support systems, visual analytics of large data sets, linked data and semantic technologies, supervised classification on data streams, and knowledge reuse in large organizations.

On the Complexity of Requirements Engineering for Decision-Support Systems: The CID Case Study.- Multi-perspective Analysis of Mobile Phone Call Data Records: A Visual Analytics Approach.- From the Web of Documents to the Linked Data.- A Survey on Supervised Classification on Data Streams.- Knowledge Reuse: Survey of Existing Techniques and Classification Approach.

"The book would be an eye-opener to those business schools that confine discussions related to business intelligence within the boundaries of commercial corporate activities. It shows how the theme could be effectively used in a wide range of cases, along with some of the latest emerging techniques available for conducting innovative analytics." (C. K. Raju, Computing Reviews, November, 2015)

Erscheint lt. Verlag 23.4.2015
Reihe/Serie Lecture Notes in Business Information Processing
Zusatzinfo IX, 149 p. 59 illus.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 266 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Schlagworte Big Data • Business Intelligence • Business Intelligence / Unternehmensintelligenz • business process management • Decision-support Systems • Incremental Learning Algorithms • knowledge management • linked data • Linked Data • machine learning • RDF • resource description framework • Stream Data • Visual Analytics
ISBN-10 3-319-17550-5 / 3319175505
ISBN-13 978-3-319-17550-8 / 9783319175508
Zustand Neuware
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