This paper presents an adaptive algorithm for learning the user profile. The user profile is learned incrementally and continuously based on user’s initial profile, his actions and on semantic interpretation of queries using hypernyms extracted by WordNet. A novel model, time words vector hyperspace, is introduced in order to keep track of the user’s interests changes. This new model is achieve...

In this paper, the chaotic behavior of a set-valued mapping F : X → 2 , where X is a compact space, is investigated. The existence of the generalized shadowing property in the hyperspace 2 is proved. Based on the generalized shadowing property of the set-valued mappings F and the assumption of the existence of an unstable chain recurrent point of the mapping F , it is shown that the Bernoulli s...

This paper addresses some particular issues related to the difficult task of automatically structuring information available in ill-structured environments, through a distributed hypermedia system like the Web. We present an original approach to this problem, which coordinates different aspects of automatic computation of relations between nodes in hyperspace, through dynamic linking, using int...

An algorithm based on a support vector machine (SVM) is proposed for hydrometeor classification. The training phase is driven by the output of a fuzzy logic hydrometeor classification algorithm, i.e., the most popular approach for hydrometer classification algorithms used for ground-based weather radar. The performance of SVM is evaluated by resorting to a weather scenario, generated by a weath...

Lexical semantic space models have recently been investigated to automatically derive the meaning (semantics) of information based on natural language usage. In a semantic space, a term can be considered as a concept represented geometrically as a vector, the components of which correspond to terms in a vocabulary. A primary way to perform reasoning in a semantic space is to categorize concepts...