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Analysis and Validation of Information Access Through Mono, Multidimensional and Dynamic Taxonomies

  • Giovanni Maria Sacco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4027)

Abstract

Access to complex information bases through multidimensional, dynamic taxonomies (also improperly known as faceted classification systems) is rapidly becoming pervasive in industry, especially in e-commerce. In this paper, the major shortcomings of conventional, monodimensional taxonomic approaches, such as the independence of different branches of the taxonomy and insufficient scalability, are discussed. The dynamic taxonomy approach, the first and most complete model for multidimensional taxonomic access to date, is reviewed and compared to conventional taxonomies. We analyze the reducing power of dynamic taxonomies and conventional taxonomies and report experimental results on real data, which confirm that monodimensional taxonomies are not useful for browsing/retrieval on large databases, whereas dynamic taxonomies can effectively manage very large databases and exhibit a very fast convergence.

Keywords

Information Base Information Access Maximum Resolution Facet Classification Boolean Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Giovanni Maria Sacco
    • 1
  1. 1.Dipartimento di InformaticaUniversità di TorinoTorinoItaly

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