Currently, and in the foreseeable future, the amount of text in electronic form is multiplying. While retrieval of this text is facilitated by increased indexing, there is a danger of overwhelming the user with too much information. As well, the current rise in available computing power means that we can consider computationally intense solutions. One such solution is dynamic taxonomy. Dynamic taxonomy uses an ontology based index, giving it the ontological advantages of structure, and increased number of interconnections. Subsequent complexity is managed by dynamic pruning.

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 Keywords

Government e-services available to citizens represent one of the most frequent and critical points of contact between public administrations and citizens. In addition to common services such as id cards, permits, e-services represent the only practical way of providing incentives and support to specific classes of citizens. For this reason, discovery of e-services, rather than plain retrieval, is a critical functionality in e-government systems. The solution we present in this paper is based on dynamic taxonomies, a semantic model for the transparent, guided, user-centric exploration of complex information bases. It provides a single framework for the access and exploration of all e-government information and, differently from mainstream research in semantic web, it is intended for the direct use of end-users, rather than for programmatic or agent-mediated access.

Dynamic taxonomies integrated into e-learning tools play a double role: on the one hand they are a powerful retrieval system in the usually large content base of an e-learning environment, on the other hand they allow and strongly encourage orthogonal visits of available learning resources by exploiting associations the user would not have thought of (and which are the specific contribution of dynamic taxonomies). These two roles are of interest both for teachers, who may use the search engine to retrieve hints for presentations, assignments, etc., and for students, who may explore the whole learning environment in a new profitable way, which makes, for example, immediately available for a same subject different aspects dealt with in different courses. In the paper we describe the integration of dynamic taxonomies into Moodle, a Course Management System for cooperative learning. 1.