Analyzing and Visualizing State Sequences in R with TraMineR

This article describes the many capabilities offered by the TraMineR toolbox for categorical sequence data. It focuses more specifically on the analysis and rendering of state sequences. Addressed features include the description of sets of sequences by means of transversal aggregated views, the computation of longitudinal characteristics of individual sequences and the measure of pairwise dissimilarities. Special emphasis is put on the multiple ways of visualizing sequences. The core element of the package is the state se- quence object in which we store the set of sequences together with attributes such as the alphabet, state labels and the color palette. The functions can then easily retrieve this information to ensure presentation homogeneity across all printed and graphical displays. The article also demonstrates how TraMineRâÂÂs outcomes give access to advanced analyses such as clustering and statistical modeling of sequence data.

An Ontology-Based Method for Semantic Integration of Business Components

Building new business information systems from reusable components is today an approach widely adopted and used. Using this approach in analysis and design phases presents a great interest and requires the use of a particular class of components called Business Components (BC). Business Components are today developed by several manufacturers and are available in many repositories. However, reusing and integrating them in a new Information System requires detection and resolution of semantic conflicts. Moreover, most of integration and semantic conflict resolution systems rely on ontology alignment methods based on domain ontology. This work is positioned at the intersection of two research areas: Integration of reusable Business Components and alignment of ontologies for semantic conflict resolution. Our contribution concerns both the proposal of a BC integration solution based on ontologies alignment and a method for enriching the domain ontology used as a support for alignment.Comment: IEEE New Technologies of Distributed Systems (NOTERE), 2011 11th Annual International Conference; ISSN: 2162-1896 Print ISBN: 978-1-4577-0729-2 INSPEC Accession Number: 12122775 201

Evaluation de Techniques de Traitement des Refusés pour l'Octroi de Crédit

We present the problem of "Reject Inference" for credit acceptance. Because of the current legal framework (Basel II), credit institutions need to industrialize their processes for credit acceptance, including Reject Inference. We present here a methodology to compare various techniques of Reject Inference and show that it is necessary, in the absence of real theoretical results, to be able to produce and compare models adapted to available data (selection of "best" model conditionnaly on data). We describe some simulations run on a small data set to illustrate the approach and some strategies for choosing the control group, which is the only valid approach to Reject Inference

Evaluation de la détection des émotions, des opinions ou des sentiments : dictatute de la majorité ou respect de la diversité d'opinions ?

National audienceDétection d'émotion, fouille d'opinion et analyse des sentiments sont généralement évalués par comparaison des réponses du système concerné par rapport à celles contenues dans un corpus de référence. Les questions posées dans cet article concernent à la fois la définition de la référence et la fiabilité des métriques les plus fréquemment utilisées pour cette comparaison. Les expérimentations menées pour évaluer le système de détection d'émotions EmoLogus servent de base de réflexion pour ces deux problèmes. L'analyse des résultats d'EmoLogus et la comparaison entre les différentes métriques remettent en cause le choix du vote majoritaire comme référence. Par ailleurs elles montrent également la nécessité de recourir à des outils statistiques plus évolués que ceux généralement utilisés pour obtenir des évaluations fiables de systèmes qui travaillent sur des données intrinsèquement subjectives et incertaines

The automatic identification system of maritime accident risk using rule-based reasoning

International audienceCurrent maritime traffic monitoring systems are not sufficiently adapted to the identification of maritime accident risk. It is very difficult for operators responsible for monitoring traffic to identify which vessels are at risk among all the shipping traffic displayed on their screen. They are overwhelmed by huge amount of kinematic ship data to be decoded. To improve this situation, this paper proposes a system for the automatic identification of maritime accident risk. The system consists of two modules. The first automates expert knowledge acquisition through the computerized exploration of historical maritime data, and the second provides a rule-based reasoning mechanism