This paper presents and experiments a new approach for automatic word sense disambiguation (WSD) applied for French texts. First, we are inspired from possibility theory by taking advantage of a double relevance measure (possibility and necessity) between words and their contexts. Second, we propose, analyze and compare two different training methods: judgment and dictionary based training. Thi...

Object-oriented remote sensing software provides the user with flexibility in the way that remotely sensed data are classified through segmentation routines and userspecified fuzzy rules. This letter explores the classification and uncertainty issues associated with aggregating detailed ‘sub-objects’ to spatially coarser ‘super-objects’ in object-oriented classifications. We show Possibility Th...

Possibilistic logic is a weighted logic introduced and developed since the mid-1980s, in the setting of arti(cial intelligence, with a view to develop a simple and rigorous approach to automated reasoning from uncertain or prioritized incomplete information. Standard possibilistic logic expressions are classical logic formulas associated with weights, interpreted in the framework of possibility...

Possibilistic ATMS are truth maintenance systems oriented towards hypothetical reasoning where both assumptions and justifications can bear an uncertainty weight. Uncertainty is represented in the framework of possibility theory. In possibilistic logic uncertain clauses are handled as such and then in possibilistic ATMS the management of uncertainty is not separated from the other classical cap...

The main purpose of this paper is to present a possibility theory-based generalization of conventional interval propagation to coverage intervals. Indeed, the whole set of coverage intervals for all the probability levels stacked on top of one another constitutes a possibility distribution. Thus by slight modifications of Zadeh’s extension principle, we will prove that it is possible to compute...

This paper proposes a discussion of inconsistency-tolerant consequence relations in prioritized knowledge bases. These inference techniques extend methods for reasoning from inconsistent, non-stratified, knowledge bases to the case where priorities between formulas are available. Priorities between formulas are handled in the framework of possibility theory and allow for the use of pieces of in...

This paper presents an approach for developing the explanation capabilities of rule-based expert systems managing imprecise and uncertain knowledge. The treatment of uncertainty takes place in the framework of possibility theory where the available information concerning the value of a logical or numerical variable is represented by a possibility distribution which restricts its more or less po...

Possibilistic logic is an important uncertainty reasoning mech anism based on Zadeh s possibility theory and classical logic The deduc tion rules of possibilistic logic have been obtained from classical resolu tion rule by attaching possibility or necessity weight to ordinary clauses However since not all possibility valued formulae can be converted into equivalent possibilistic clauses the res...

The probabilistic Noisy OR model has been widely used as a means of reducing the amount of probabilistic information that is needed to specify the interaction between groups of variables. Motivated by our work on the diagnosis of faults in satellite subsystems , which required a similar synthesis of partial possibilistic information on interactions , we consider a number of ways of gener-alisin...

This paper presents further work on a 3D visualisation system for the reconstruction of historical structures which takes into account archaeological uncertainty. The uncertainty associated with an archaeologist’s interpretation is represented using possibility theory and visualised by shader-based information visualisation schemes. An increase or decrease in uncertainty is influenced by any re...