La constitution du TAL: Étude historique des dénominations et des concepts

Several terms have been in competition as names for the theoretical and applieddiscipline that lies in the intersection of linguistics, mathematics, computer sciences andcognitive sciences and which developed out of early experiments in Machine Translation.They include Computational Linguistics and Natural Language Processing in English, andTraitement automatique des langues, Informatique linguistique and Linguistique informatiquein French. This paper traces the history of these terms and considers whether theterminological variation may be a symptom of the conflicts at work in the field, concerningthe institutional, economical, theoretical and conceptual issues.Pour désigner le champ d'investigations et d'applications à l'intersection de lalinguistique, des mathématiques, de l'informatique et des sciences cognitives hérité desexpériences pionnières en traduction automatique, plusieurs termes sont ou ont été enconcurrence, Computational Linguistics ou Natural Language Processing dans le domaineanglo-américain, Traitement automatique des langues, Informatique linguistique ouLinguistique informatique en France. Cet article se propose, en retraçant le parcourshistorique de ces dénominations, de montrer que le flottement sur les termes estsymptomatique des tensions à l'oeuvre dans le domaine, sur le plan des enjeux institutionnels,économiques, théoriques et conceptuels

Introduction

L'ouvrage interroge, pour la première fois en France de manière aussi explicite, la question de la relation entre l'analyse de discours et la demande sociale ...

Hyperspectral images segmentation: a proposal

Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous wavebands in a given spectral band. These images provide information on the chemical make-up profile of objects, thus allowing the differentiation of objects of the same colour but which possess make-up profile. Yet, whatever the application field, most of the methods devoted to HIS processing conduct data analysis without taking into account spatial information.Pixels are processed individually, as an array of spectral data without any spatial structure. Standard classification approaches are thus widely used (k-means, fuzzy-c-means hierarchical classification...). Linear modelling methods such as Partial Least Square analysis (PLS) or non linear approaches like support vector machine (SVM) are also used at different scales (remote sensing or laboratory applications). However, with the development of high resolution sensors, coupled exploitation of spectral and spatial information to process complex images, would appear to be a very relevant approach. However, few methods are proposed in the litterature. The most recent approaches can be broadly classified in two main categories. The first ones are related to a direct extension of individual pixel classification methods using just the spectral dimension (k-means, fuzzy-c-means or FCM, Support Vector Machine or SVM). Spatial dimension is integrated as an additionnal classification parameter (Markov fields with local homogeneity constrainst [5], Support Vector Machine or SVM with spectral and spatial kernels combination [2], geometrically guided fuzzy C-means [3]...). The second ones combine the two fields related to each dimension (spectral and spatial), namely chemometric and image analysis. Various strategies have been attempted. The first one is to rely on chemometrics methods (Principal Component Analysis or PCA, Independant Component Analysis or ICA, Curvilinear Component Analysis...) to reduce the spectral dimension and then to apply standard images processing technics on the resulting score images i.e. data projection on a subspace. Another approach is to extend the definition of basic image processing operators to this new dimensionality (morphological operators for example [1, 4]). However, the approaches mentioned above tend to favour only one description either directly or indirectly (spectral or spatial). The purpose of this paper is to propose a hyperspectral processing approach that strikes a better balance in the treatment of both kinds of information....Cet article présente une stratégie de segmentation d’images hyperspectrales liant de façon symétrique et conjointe les aspects spectraux et spatiaux. Pour cela, nous proposons de construire des variables latentes permettant de définir un sous-espace représentant au mieux la topologie de l’image. Dans cet article, nous limiterons cette notion de topologie à la seule appartenance aux régions. Pour ce faire, nous utilisons d’une part les notions de l’analyse discriminante (variance intra, inter) et les propriétés des algorithmes de segmentation en région liées à celles-ci. Le principe générique théorique est exposé puis décliné sous la forme d’un exemple d’implémentation optimisé utilisant un algorithme de segmentation en région type split and merge. Les résultats obtenus sur une image de synthèse puis réelle sont exposés et commentés

From Models to Simulations

This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how and why computers, data treatment devices and programming languages have occasioned a gradual but irresistible and massive shift from mathematical models to computer simulations

Modélisation dune Interaction Didactique Distante Individuelle Synchrone (ID2IS)

Notre objectif est de saisir la complexité " temps réel " d'une interaction didactique médiée par ordinateur. Les expérimentations, instrumentées par un dispositif de visiocommunication et de partage d'environnement de travail, nous ont conduit à préciser les influences concomitantes des déterminants technologiques et humains sur une interaction caractérisée par deux processus : enseigner et apprendre. La spécificité de notre démarche consiste à mettre en synergie cette approche (inhérente aux champs IHM & CSCW), avec l'approche systémique du didacticien. Cela nous permet de modéliser graduellement l'interface du dispositif, l'environnement de chacun des acteurs et l'univers partagé par les acteurs aux différentes phases de l'interaction. Cette modélisation, formalisée au moyen du logiciel MOT, est appliquée à l'interprétation d'une interaction en géométrie supportée par Cabrigéomètre

Analysis of Quickselect under Yaroslavskiy's Dual-Pivoting Algorithm

There is excitement within the algorithms community about a new partitioning method introduced by Yaroslavskiy. This algorithm renders Quicksort slightly faster than the case when it runs under classic partitioning methods. We show that this improved performance in Quicksort is not sustained in Quickselect; a variant of Quicksort for finding order statistics. We investigate the number of comparisons made by Quickselect to find a key with a randomly selected rank under Yaroslavskiy's algorithm. This grand averaging is a smoothing operator over all individual distributions for specific fixed order statistics. We give the exact grand average. The grand distribution of the number of comparison (when suitably scaled) is given as the fixed-point solution of a distributional equation of a contraction in the Zolotarev metric space. Our investigation shows that Quickselect under older partitioning methods slightly outperforms Quickselect under Yaroslavskiy's algorithm, for an order statistic of a random rank. Similar results are obtained for extremal order statistics, where again we find the exact average, and the distribution for the number of comparisons (when suitably scaled). Both limiting distributions are of perpetuities (a sum of products of independent mixed continuous random variables).Comment: full version with appendices; otherwise identical to Algorithmica versio