000 | 03918nam a22005535i 4500 | ||
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001 | 978-3-319-05461-2 | ||
003 | DE-He213 | ||
005 | 20170628034128.0 | ||
007 | cr nn 008mamaa | ||
008 | 140320s2014 gw | s |||| 0|eng d | ||
020 |
_a9783319054612 _9978-3-319-05461-2 |
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024 | 7 |
_a10.1007/978-3-319-05461-2 _2doi |
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050 | 4 | _aHF54.5-54.56 | |
072 | 7 |
_aKJQ _2bicssc |
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_aUF _2bicssc |
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_aBUS083000 _2bisacsh |
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_aCOM039000 _2bisacsh |
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082 | 0 | 4 |
_a650 _223 |
100 | 1 |
_aZimányi, Esteban. _eeditor. |
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245 | 1 | 0 |
_aBusiness Intelligence _h[electronic resource] : _bThird European Summer School, eBISS 2013, Dagstuhl Castle, Germany, July 7-12, 2013, Tutorial Lectures / _cedited by Esteban Zimányi. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
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300 |
_aIX, 243 p. 95 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Business Information Processing, _x1865-1348 ; _v172 |
|
505 | 0 | _aIntroduction to Pattern Mining -- Process Mining in the Large: A Tutorial -- Ontology-Driven Business Intelligence for Comparative Data Analysis -- Open Access Semantic Aware Business Intelligence -- Transparent Forecasting Strategies in Database Management Systems -- On Index Structures for Star Query Processing in Data Warehouses -- Intelligent Wizard for Human Language Interaction in Business Intelligence. | |
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 Third 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., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis. 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 | _aEconomics. | |
650 | 0 | _aComputer science. | |
650 | 0 | _aData mining. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 | _aInformation systems. | |
650 | 0 | _aManagement information systems. | |
650 | 1 | 4 | _aEconomics/Management Science. |
650 | 2 | 4 | _aBusiness Information Systems. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aComputer Appl. in Administrative Data Processing. |
650 | 2 | 4 | _aProbability and Statistics in Computer Science. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319054605 |
830 | 0 |
_aLecture Notes in Business Information Processing, _x1865-1348 ; _v172 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-05461-2 |
912 | _aZDB-2-SCS | ||
999 |
_c18420 _d18420 |