Data Warehousing and Knowledge Discovery: 16th International by Ladjel Bellatreche, Mukesh K. Mohania

By Ladjel Bellatreche, Mukesh K. Mohania

This ebook constitutes the refereed lawsuits of the sixteenth foreign convention on info Warehousing and data Discovery, DaWaK 2014 held in Munich, Germany, September 2014, along with DEXA 2014. The 34 revised complete papers and eight brief papers awarded have been conscientiously reviewed and chosen from 109 submissions. The papers are equipped in topical sections on modeling and ETL; ontology-based facts warehouses; complex facts warehouses and OLAP; uncertainty; personal tastes and advice; question functionality and HPC; dice & OLAP; optimization; type; social networks and advice structures; wisdom facts discovery; commercial purposes; mining and processing information circulation; mining and similarity.

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Springer, Heidelberg (2002) 6. : Schema versioning in data warehouses: Enabling cross-version querying via schema augmentation. Data & Knowledge Engineering 59(2), 435–459 (2006) 7. : A survey on temporal data warehousing. International Journal of Data Warehousing and Mining 5(1), 1–17 (2009) 8. : The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd edn. John Wiley & Sons (2013) 9. : A conceptual model for temporal data warehouses and its transformation to the ER and the object-relational models.

LNCS, vol. 5895, pp. 199–220. : QoX-driven ETL design: Reducing the cost of ETL consulting engagements. In: SIGMOD, pp. 953–960. : Leveraging business process models for ETL design. , Wand, Y. ) ER 2010. LNCS, vol. 6412, pp. 15–30. Springer, Heidelberg (2010) A Logical Model for Multiversion Data Warehouses Waqas Ahmed1, , Esteban Zim´anyi1 , and Robert Wrembel2, 1 Dept. pl Abstract. Data warehouse systems integrate data from heterogeneous sources. These sources are autonomous in nature and change independently of a data warehouse.

One of its outputs is the conceptual MD model. Another approach is the Advanced DW [7], which adds spatial and temporal meta-concepts to the ER language. To enforce the semantics in MD design, Romero et al. [11] propose an approach based on end-user requirements elicitation, representing the data sources as domain L. K. ): DaWaK 2014, LNCS 8646, pp. 35–44, 2014. © Springer International Publishing Switzerland 2014 36 J. Moreira et al. ontology. From this, MD concepts (facts, measures, dimensions, hierarchies and attributes) are identified based on functional dependencies.

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