A descriptive approach to classification

Abstract

Nowadays information systems are required to be more adaptable and flexible than before to deal with the rapidly increasing quantity of available data and changing information needs. Text Classification (TC) is a useful task that can help to solve different problems in different fields. This paper investigates the application of descriptive approaches for modelling classification. The main objectives are increasing abstraction and flexibility so that expert users are able to customise specific strategies for their needs. The contribution of this paper is two-fold. Firstly, it illustrates that the modelling of classifiers in a descriptive approach is possible and it leads to a close definition w.r.t. mathematical formulations. Moreover, the automatic translation from PDatalog to mathematical formulation is discussed. Secondly, quality and efficiency results prove the approach feasibility for real-scale collections. © 2011 Springer-Verlag.