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Titlebook: Business Intelligence; Second European Summ Marie-Aude Aufaure,Esteban Zimányi Textbook 2013 Springer-Verlag GmbH Germany, part of Springer

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樓主: purulent
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發(fā)表于 2025-3-23 09:43:43 | 只看該作者
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發(fā)表于 2025-3-23 14:53:57 | 只看該作者
https://doi.org/10.1007/978-1-4612-2286-6tandard data models and system implementations (OLAP) for multidimensional databases are sometimes not able to capture the complexities of advanced real-world application domains. This lecture will focus on how to manage such complex multidimensional data, including complex dimension hierarchies, co
13#
發(fā)表于 2025-3-23 20:42:27 | 只看該作者
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發(fā)表于 2025-3-24 00:09:54 | 只看該作者
Sandra Jeppesen,Paola Sartorettoormal way and examined for their significance in the broader context of statistical relational learning approaches in general and Bayesian logic networks in particular. A sandbox example is discussed in order to explain in detail the meanings of input theories with weighted clauses for a MLN. Then,
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發(fā)表于 2025-3-24 05:22:29 | 只看該作者
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發(fā)表于 2025-3-24 06:59:48 | 只看該作者
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發(fā)表于 2025-3-24 14:32:58 | 只看該作者
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發(fā)表于 2025-3-24 17:27:38 | 只看該作者
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發(fā)表于 2025-3-24 22:10:46 | 只看該作者
20#
發(fā)表于 2025-3-25 00:35:28 | 只看該作者
Managing Complex Multidimensional Data,mplex measures, and integration of multidimensional data with complex external data. We will look at how complex multidimensional data emerge in complex application domains such as medical data, location-based services, music data, web data, and text data, and present solutions for these domains that support multidimensional business intelligence.
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