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SKDQL: A Structured Language to Specify Knowledge Discovery Processes and Queries

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Advances in Artificial Intelligence – SBIA 2004 (SBIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3171))

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Abstract

Tools and techniques used for automatic and smart analysis of huge data repositories of industries, governments, corporations and scientific institutes are the subjects dealt by the field of Knowledge Discovery in Databases (KDD). In MATRIKS context, a framework for KDD, SKDQL (Structured Knowledge Discovery Query Language) is the proposal of a structured language for KDD specification, following SQL patterns within an open and extensible architecture, supporting heterogeneity, interaction and increment of KDD process, with resources for accessing, cleaning, transforming, deriving and mining data, beyond knowledge manipulation.

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Author information

Authors and Affiliations

  1. Universidade do Estado do Rio Grande do Norte, BR 110, Km 48, 59610-090, Mossoró, RN, Brasil

    Marcelino Pereira dos Santos Silva

  2. Centro de Informática, Universidade Federal de Pernambuco, 50670-901, Recife, PE, Brasil

    Jacques Robin

Authors
  1. Marcelino Pereira dos Santos Silva
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  2. Jacques Robin
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Editor information

Editors and Affiliations

  1. Instituto de Informática, UFRGS, Porto Alegre, RS, Brasil

    Ana L. C. Bazzan

  2. Intelligent Systems Laboratory LSI, Center of Technology, Federal University of Maranao UFMA, Bacanga Campus, 65080-040, Sao Luis, MA, Brazil

    Sofiane Labidi

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© 2004 Springer-Verlag Berlin Heidelberg

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dos Santos Silva, M.P., Robin, J. (2004). SKDQL: A Structured Language to Specify Knowledge Discovery Processes and Queries. In: Bazzan, A.L.C., Labidi, S. (eds) Advances in Artificial Intelligence – SBIA 2004. SBIA 2004. Lecture Notes in Computer Science(), vol 3171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28645-5_33

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  • DOI: https://doi.org/10.1007/978-3-540-28645-5_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23237-7

  • Online ISBN: 978-3-540-28645-5

  • eBook Packages: Springer Book Archive

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