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Mapping and Integration of Dimensional Attributes Using Clustering Techniques

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E-Commerce and Web Technologies (EC-Web 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 123))

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Abstract

Following recent trends in Data Warehousing, companies realized that there is a great potential in combining their information repositories to obtain a broader view of the economical market. Unfortunately, even though Data Warehouse (DW) integration has been defined from a theoretical point of view, until now no complete, widely used methodology has been proposed to support the integration of the information coming from heterogeneous DWs. This paper deals with the automatic integration of dimensional attributes from heterogeneous DWs. A method relying on topological properties that similar dimensions maintain is proposed for discovering mappings of dimensions, and a technique based on clustering algorithms is introduced for integrating the data associated to the dimensions.

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Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Modena and Reggio Emilia, Via Vignolese 905, 41025, Modena, Italy

    Francesco Guerra, Marius-Octavian Olaru & Maurizio Vincini

Authors
  1. Francesco Guerra
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  2. Marius-Octavian Olaru
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  3. Maurizio Vincini
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Editor information

Editors and Affiliations

  1. Institute of Software Technology and Interactive Systems, Business Informatics Group (BIG), Vienna University of Technology, Favoritenstrasse 9 - 11 / 188-3, 1040, Vienna, Austria

    Christian Huemer

  2. Dipartimento di Informatica, Università di Bari, Via E. Orabona, 4, I70126, Bari, Italy

    Pasquale Lops

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© 2012 Springer-Verlag Berlin Heidelberg

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Guerra, F., Olaru, MO., Vincini, M. (2012). Mapping and Integration of Dimensional Attributes Using Clustering Techniques. In: Huemer, C., Lops, P. (eds) E-Commerce and Web Technologies. EC-Web 2012. Lecture Notes in Business Information Processing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32273-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-32273-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32272-3

  • Online ISBN: 978-3-642-32273-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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