Business Intelligence Second European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures /

To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the "Big Data" phenom...

Full description

Bibliographic Details
Published in:Springer eBooks
Corporate Author: SpringerLink (Online service)
Other Authors: Aufaure, Marie-Aude (Editor), Zimányi, Esteban (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series:Lecture Notes in Business Information Processing,
Subjects:
Online Access:http://dx.doi.org/10.1007/978-3-642-36318-4
Перейти в каталог НБ ТГУ
LEADER 04725nam a22006135i 4500
001 vtls000484699
003 RU-ToGU
005 20210922070224.0
007 cr nn 008mamaa
008 140715s2013 gw | s |||| 0|eng d
020 |a 9783642363184  |9 978-3-642-36318-4 
024 7 |a 10.1007/978-3-642-36318-4  |2 doi 
035 |a to000484699 
039 9 |y 201407151947  |z Александр Эльверович Гилязов 
040 |a Springer  |c Springer  |d RU-ToGU 
050 4 |a HF54.5-54.56 
072 7 |a KJQ  |2 bicssc 
072 7 |a UF  |2 bicssc 
072 7 |a BUS083000  |2 bisacsh 
072 7 |a COM039000  |2 bisacsh 
082 0 4 |a 650  |2 23 
100 1 |a Aufaure, Marie-Aude.  |e editor.  |9 417021 
245 1 0 |a Business Intelligence  |h [electronic resource] :  |b Second European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures /  |c edited by Marie-Aude Aufaure, Esteban Zimányi. 
260 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013.  |9 742158 
300 |a X, 235 p. 83 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Lecture Notes in Business Information Processing,  |x 1865-1348 ;  |v 138 
505 0 |a Managing Complex Multidimensional Data -- An Introduction to Business Process Modeling -- Machine Learning Strategies for Time Series Forecasting -- Knowledge Discovery from Constrained Relational Data: A Tutorial on Markov Logic Networks -- Large Graph Mining: Recent Developments, Challenges and Potential Solutions -- Big Data Analytics on Modern Hardware Architectures: A Technology Survey -- An Introduction to Multicriteria Decision Aid: The PROMETHEE and GAIA Methods -- Knowledge Harvesting for Business Intelligence -- Business Semantics as an Interface between Enterprise Information Management and the Web of Data: A Case Study in the Flemish Public Administration. 
520 |a To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the "Big Data" phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors', suppliers', or distributors' data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into account location-based or time-based environmental data. The lectures held at the Second European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI and BPM technologies, but extend into innovative aspects that are important in this new environment and for novel applications, e.g., machine learning, logic networks, graph mining, business semantics, large-scale data management and analysis, and multicriteria and collaborative decision making. Combining papers by leading researchers in the field, this volume equips the reader with the state-of-the-art background necessary for creating the future of BI. It also provides the reader with an excellent basis and many pointers for further research in this growing field. 
650 0 |a Economics.  |9 135154 
650 0 |a Computational complexity.  |9 304814 
650 0 |a Computer Science.  |9 155490 
650 0 |a Database management.  |9 566224 
650 0 |a Information storage and retrieval systems.  |9 137013 
650 0 |a Information systems.  |9 303226 
650 0 |a Management information systems.  |9 299049 
650 1 4 |a Economics/Management Science.  |9 247365 
650 2 4 |a Business Information Systems.  |9 299050 
650 2 4 |a Computer Appl. in Administrative Data Processing.  |9 307999 
650 2 4 |a Database Management.  |9 566226 
650 2 4 |a Information Storage and Retrieval.  |9 303027 
650 2 4 |a Discrete Mathematics in Computer Science.  |9 304816 
650 2 4 |a Probability and Statistics in Computer Science.  |9 304554 
700 1 |a Zimányi, Esteban.  |e editor.  |9 322157 
710 2 |a SpringerLink (Online service)  |9 143950 
773 0 |t Springer eBooks 
830 0 |a Lecture Notes in Business Information Processing,  |9 299056 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-36318-4 
856 |y Перейти в каталог НБ ТГУ  |u https://koha.lib.tsu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=358177 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645) 
999 |c 358177  |d 358177