The angular gyrus (AG) and anterior temporal lobe (ATL) have been found to respond to a number of tasks involving combinatorial processing. In this study, we investigate the conceptual combination of nominal compounds, and ask whether ATL/AG activity is modulated by the type of combinatorial operation applied to a nominal compound. We compare relational and attributive interpretations of nomina...

This paper surveys terminological representation languages and feature-based unification grammars pointing out the similarities and differences between these two families of attributive description formalisms. Emphasis is given to the logical foundations of these formalisms.

There is currently an increased interest in workers health. Retraining due to illness is the topic of this study. The objective of this qualitative study was to understand how individuals cope with job retraining in a public hospital, utilizing interviews to understand how nursing professionals coped with the retraining process, which were then analyzed using Content Analysis as proposed by Bar...

Research in knowledge representation has led to the development of so-called terminological logics, the purpose of which is to support the representation of the conceptual and terminological part of Artificial Intelligence applications. Independently, in computational linguistics, so-called feature logics have been developed which are aimed at representing the semantic and syntactic information...

In well-behaved cases of adjectival modification, the adjective-noun sequence describes a firstorder property whose content is fully determined by the contents of the adjective and the noun. For example, the truth conditions of They hired a vegetarian dentist, They hired a former linguist, and They hired an electrical engineer, are functions of the property of being a vegetarian dentist, of bei...

In this paper an unsupervised scheme for stereoscopic video object extraction is presented based on a neural network classifier. More particularly, the procedure includes: (A) A retraining algorithm for adapting neural network weights to current conditions and (B) An active contour module, which extracts the retraining set. The retraining algorithm takes into consideration both the former and t...

This paper addresses the problem of semi-supervised classification on document collections using retraining (also called self-training). A possible application is focused Web crawling which may start with very few, manually selected, training documents but can be enhanced by automatically adding initially unlabeled, positively classifiedWeb pages for retraining. Such an approach is by itself no...