Multivariate pattern analysis is a technique that allows the decoding of conceptual information such as the semantic category of a perceived object from neuroimaging data. Impressive single-trial classification results have been reported in studies that used fMRI. Here, we investigate the possibility to identify conceptual representations from event-related EEG based on the presentation of an o...

The evolution of information systems from their conceptual schemas is an important research area in information systems engineering. In this paper, we aim at contributing to the area by focusing on a particular conceptual modeling construct, the partitions. We analyze the evolution of partitions in conceptual schemas of information systems. We deal with conceptual models with multiple specializ...

In conceptual modelling, there are many competing views of the role of the modelling language. In this paper, we propose a clarifying classification of different kinds of languages. This classification, based on the semantical background theory of each kind of language, divides the modelling languages into three categories: extensional modelling languages, languages based on concept calculus (i...

The exponential growth of text available on the Internet has created a critical need for accurate, fast, and generalpurpose text classification algorithms. This paper examines the improvement of broadly based text classification by using features that are easily extracted from training documents. These features represent both the conceptual and contextual properties of a target class, and inclu...

Subjects studied words in a classification task (to what categories does it belong?) or in a production task (producing associates to the word) and then completed one of two implicit memory tests-category association or free association. The classification study task and the category-association test emphasize categorical relations between concepts, and the production study task and the free-as...