Most Natural Language Processing (NLP) systems traditionally use a sequential architecture that represents the classical linguistic levels (lexical-morphological, syntactical, semantic, etc.), but they claim for huge and monolithic modules, that make the backtracking among such modules difficult. By using a…

Purpose – The idea that knowledge management can be a potential source of competitive advantage has gained strength in the last few years. However, a number of business actions are needed to generate an appropriate environment and infrastructure for knowledge…

This paper focuses on the general problem of the lexical bottleneck and, in particular, on the issues of semantic clustering and disambiguation by means of word usage cues obtained from sublanguage-specific corpora. Our approaches combines the use of numerical techniques…

This work presents the main theories and models formulated with the purpose of offering a global overview on the acquisition of knowledge and skills involved in the initial development of expert competence. Setting from this background, we developed an empirical…

We develop a theory to explain the transition from stagnation to modern growth. We focus on the forces that shaped the evolution of total factor productivity in agriculture and manufacturing across history. More specifically, we build a multisector model of…

Diagnosis is an important process in patient care. A suitable diagnosis helps a physician determine a precise treatment. Physicians also have a tendency to seek collaboration from other colleagues and expert systems for better confidence in their decision. The sources…

In this paper, a method of event ordering based on temporal information resolution is presented. This method consists of two main steps: on the one hand, the recognition and resolution of the temporal expressions that can be transformed on a…

In this paper, a method to combine visual and force information using the
information obtained from the movement flow-based visual servoing system is proposed. This
method allows not only to achieve a given desired position but also to specify the…

The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from…

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the…