Several systems for the management of digital libraries have evolved in the recent past from simple document repository to sophisticated applications that provide the possibility of classifying and, in some cases, even rating the documents collected in the library itself. In a few of those systems members of the community of practice that uses and produces the library itself can also be active in assigning a reputation score to each other. This study aimed to explore the idea of using a collectively negotiated term taxonomy in order to develop a better model for the automated evaluation of users' competence on different discussion topics. Design/methodology/approach - The study provides a formalization of the approach we propose, and the proposal of an architecture for implementing a system deploying the approach. Findings - The study analyses the issues related to the implementation of a digital library, and develops an architecture that aims to evaluate users' competence about different discussion topics in an automated way. Research limitations/implications - The paper only describes an abstract architecture of a self-balancing digital library. Further research should investigate the different possible choices for the implementation details that have been left out from this first explorative analysis. Originality/value - The novelty of the approach resides in the fact that we make use of a collectively negotiated taxonomy in order to automatically assign relevance scores to reviewers' evaluations.
|Titolo:||A cooperative environment for the negotiation of term taxonomies in digital libraries|
|Data di pubblicazione:||2005|
|Appare nelle tipologie:||01.01 Articolo in Rivista|