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020 _a9783642363184
_9978-3-642-36318-4
024 7 _a10.1007/978-3-642-36318-4
_2doi
050 4 _aHF54.5-54.56
072 7 _aKJQ
_2bicssc
072 7 _aUF
_2bicssc
072 7 _aBUS083000
_2bisacsh
072 7 _aCOM039000
_2bisacsh
082 0 4 _a650
_223
082 0 4 _a658.05
_223
245 1 0 _aBusiness Intelligence
_h[electronic resource] :
_bSecond European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures /
_cedited by Marie-Aude Aufaure, Esteban Zimányi.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aX, 235 p. 83 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Business Information Processing,
_x1865-1348 ;
_v138
505 0 _aManaging 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 _aTo 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 _aBusiness.
650 0 _aInformation technology.
650 0 _aBusiness
_xData processing.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aDatabase management.
650 0 _aInformation storage and retrieval.
650 0 _aApplication software.
650 1 4 _aBusiness and Management.
650 2 4 _aIT in Business.
650 2 4 _aComputer Appl. in Administrative Data Processing.
650 2 4 _aDatabase Management.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aProbability and Statistics in Computer Science.
700 1 _aAufaure, Marie-Aude.
_eeditor.
700 1 _aZimányi, Esteban.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642363177
830 0 _aLecture Notes in Business Information Processing,
_x1865-1348 ;
_v138
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-36318-4
912 _aZDB-2-SCS
942 _2Dewey Decimal Classification
_ceBooks
999 _c46781
_d46781