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

Access to complex information bases through multidimensional, dynamic taxonomies (also improperly known as faceted classifications) is becoming a hot concept both in research and in industry. 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. ACM Classification