Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Business Information Processing (LNBIP, volume 205)
Included in the following conference series:
Conference proceedings info: eBISS 2014.
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Table of contents (5 chapters)
Keywords
About this book
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.
Reviews
“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)
Editors and Affiliations
Bibliographic Information
Book Title: Business Intelligence
Book Subtitle: 4th European Summer School, eBISS 2014, Berlin, Germany, July 6-11, 2014, Tutorial Lectures
Editors: Esteban Zimányi, Ralf-Detlef Kutsche
Series Title: Lecture Notes in Business Information Processing
DOI: https://doi.org/10.1007/978-3-319-17551-5
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2015
Softcover ISBN: 978-3-319-17550-8Published: 23 April 2015
eBook ISBN: 978-3-319-17551-5Published: 15 April 2015
Series ISSN: 1865-1348
Series E-ISSN: 1865-1356
Edition Number: 1
Number of Pages: IX, 149
Number of Illustrations: 59 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Business Information Systems, Artificial Intelligence, Computer Appl. in Administrative Data Processing, Knowledge Management