A basic component in Internet applications is the electronic mail and its various implications. The paper proposes a mechanism for automatically classifying emails and create dynamic groups that belong to these messages. Proposed mechanisms will be based on natural language processing techniques and will be designed to facilitate human-machine interaction in this direction.
Semantic Atlas is a mathematic and statistic model to visualise word senses according to relations between words. The model, that has been applied to proximity relations from a corpus, has shown its ability to distinguish word senses as the corpus co
ntributors comprehend them. We propose to use the model and a specialised corpus in order to create automatically a specialised dictionary relative to the corpus domain. A morpho-syntactic analysis performed on the corpus makes it possible to create the dictionary from syntactic relations between lexical units. The semantic resource can be used to navigate semantically - and not only lexically - through the corpus, to create classical dictionaries or for diachronic studies of the language.
SWift (SignWriting improved fast transcriber) is an advanced editor for SignWriting (SW). At present, SW is a promising alternative to provide documents in an easy-to-grasp written form of (any) Sign Language, the gestural way of communication which
is widely adopted by the deaf community. SWift was developed SW users, either deaf or not, to support collaboration and exchange of ideas. The application allows composing and saving desired signs using elementary components, called glyphs. The procedure that was devised guides and simplifies the editing process. SWift aims at breaking the electronic barriers that keep the deaf community away from ICT in general, and from e-learning in particular. The editor can be contained in a pluggable module; therefore, it can be integrated everywhere the use of SW is an advisable alternative to written verbal language, which often hinders information grasping by deaf users.
We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categorization. Unsolicited commercial e-mail, or spam, floods mailboxes, c
ausing frustration, wasting bandwidth, and exposing minors to unsuitable content. Using a public corpus, we show that stacking can improve the efficiency of automatically induced anti-spam filters, and that such filters can be used in real-life applications.
In order to compare social organization of a medieval peasantry before and after the Hundred Years War we study the sructure of social networks built from a corpus of agrarian contracts. Low diameters and high clusterings show small-world graphs. Lik
e many other networks studied these last years these graphs are scale-free. The distributions of the vertex degrees are fitted by a truncated power law. Moreover they have a rich-club : a dense core with a low diameter consisting of vertices with high degree. The particular shape of the laplacian spectrum allows us to extract communities that are spread along a star whose center is the rich-club.
We proove some inequalities concerning the product, sup * inf for some elliptic operators of order 2 and 4. Using those inequalities and the concentration phenomena we can describe the asymptotic behavior of those PDE solutions.