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Similarity-Based Classification of Microdata

In: Information Technology and Innovation Trends in Organizations

Author

Listed:
  • S. Castano

    (Università degli Studi di Milano)

  • A. Ferrara

    (Università degli Studi di Milano)

  • S. Montanelli

    (Università degli Studi di Milano)

  • G. Varese

    (Università degli Studi di Milano)

Abstract

In this paper, we propose a similarity-based approach for microdata classification based on tagging, matching and clouding techniques. The goal is to construct entity-centric microdata clouds where similar microdata items can be properly arranged to highlight their relevance with respect to a selected target entity according to different notions of relevance defined in the paper. An application example is provided, based on a microdata collection extracted from a real microblogging system.

Suggested Citation

  • S. Castano & A. Ferrara & S. Montanelli & G. Varese, 2011. "Similarity-Based Classification of Microdata," Springer Books, in: Alessandro D'Atri & Maria Ferrara & Joey F. George & Paolo Spagnoletti (ed.), Information Technology and Innovation Trends in Organizations, pages 125-132, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2632-6_15
    DOI: 10.1007/978-3-7908-2632-6_15
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