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Магистерская диссертация посвящена сопоставительному анализу терминологических словосочетаний на английском и русском языке, представляющих собой двухкомпонентные цепочки слов. Исследование проводилось на материале инструкций. Материал исследования составляет 152 термина на английском языке и 173 термина на русском языке. В ходе исследования рассмотрена специфика употребления терминов, а также теория словосочетания. Было определено, при помощи каких моделей построены англоязычные термины и их переводные соответствия; выявлены особенности использования структурных моделей при переводе словосочетаний. Результаты исследования можно использовать как материал для практических занятий по теории и практике перевода, для спецкурсов по научно-техническому переводу и др. / The master's thesis is devoted to the comparative analysis of terminological phrases in English and in Russian, which grammatically are two-component word chains. The study was carried out on the material of instruction manuals. The material of the study consists of 152 terms in English and 173 terms in Russian. In the course of the study, the peculiarities of the use of terms as well as the theory of phrases are considered. It was determined which models were used to build English-language terms and their translational correspondences; the peculiarities of the use of the structural models in the translation of phrases were identified. The results of the study can be used as a material for practical classes on the theory and practice of translation, for special courses on scientific and technical translation, etc.

On the assumption that the translation strategies used to translate American fast-food advertisements into Arabic cause the Arabic translations to be culturally bound to their originals, the aim of the present study is to identify such translation strategies. The study was conducted with the aid of questionnaires as a primary research method to obtain data which are then complemented by means of textual analyses of the corpus. The findings reveal that the main translation strategies used to translate phrases in fast-food advertisements from English into Arabic are borrowing and transliteration. The overall finding is that inadequate translations of culture-specific concepts, phrases, logos and terms produce target texts which are bound to the source texts. This causes the translations to be rejected by the target culture. / Linguistics / M.A. (Linguistics)

Le travail s'inscrit dans le domaine du traitement automatique du langage naturel et traite plus spécifiquement d'une application de ce dernier au résumé automatique de textes.<br />L'originalité de la thèse consiste à s'attaquer à une variété fort peu explorée, la compression de textes, par une technique non supervisée.<br />Ce travail propose un système incrémental et interactif d'élagage de l'arbre syntagmatique des phrases, tout en préservant la cohérence syntaxique et la conservation du contenu informationnel important.<br />Sur le plan théorique, le travail s'appuie sur la théorie du gouvernement de Noam Chomsky et plus particulièrement sur la représentation formelle de la théorie X-barre pour aboutir à un fondement théorique important pour un modèle computationnel compatible avec la compression syntaxique de phrases.<br />Le travail a donné lieu a un logiciel opérationnel, nommé COLIN, qui propose deux modalités : une compression automatique, et une aide au résumé sous forme semi-automatique, dirigée par l'interaction avec l'utilisateur.<br />Le logiciel a été évalué grâce à un protocole complexe par 25 utilisateurs bénévoles.<br />Les résultats de l'expérience montrent que 1) la notion de résumé de référence qui sert aux évaluations classiques est discutable 2) les compressions semi-automatiques ont été fortement appréciées 3) les compressions totalement automatiques ont également obtenu de bons scores de satisfaction.<br />À un taux de compression supérieur à 40% tous genres confondus, COLIN fournit un support appréciable en tant qu'aide à la compression de textes, ne dépend d'aucun corpus d'apprentissage, et présente une interface convivial.

La traduction statistique requiert des corpus parallèles en grande quantité. L’obtention de tels corpus passe par l’alignement automatique au niveau des phrases. L’alignement des corpus parallèles a reçu beaucoup d’attention dans les années quatre vingt et cette étape est considérée comme résolue par la communauté. Nous montrons dans notre mémoire que ce n’est pas le cas et proposons un nouvel aligneur que nous comparons à des algorithmes à l’état de l’art. Notre aligneur est simple, rapide et permet d’aligner une très grande quantité de données. Il produit des résultats souvent meilleurs que ceux produits par les aligneurs les plus élaborés. Nous analysons la robustesse de notre aligneur en fonction du genre des textes à aligner et du bruit qu’ils contiennent. Pour cela, nos expériences se décomposent en deux grandes parties. Dans la première partie, nous travaillons sur le corpus BAF où nous mesurons la qualité d’alignement produit en fonction du bruit qui atteint les 60%. Dans la deuxième partie, nous travaillons sur le corpus EuroParl où nous revisitons la procédure d’alignement avec laquelle le corpus Europarl a été préparé et montrons que de meilleures performances au niveau des systèmes de traduction statistique peuvent être obtenues en utilisant notre aligneur. / Current statistical machine translation systems require parallel corpora in large quantities, and typically obtain such corpora through automatic alignment at the sentence level: a text and its translation . The alignment of parallel corpora has received a lot of attention in the eighties and is largely considered to be a solved problem in the community. We show that this is not the case and propose an alignment technique that we compare to the state-of-the-art aligners. Our technique is simple, fast and can handle large amounts of data. It often produces better results than state-of-the-art. We analyze the robustness of our alignment technique across different text genres and noise level. For this, our experiments are divided into two main parts. In the first part, we measure the alignment quality on BAF corpus with up to 60% of noise. In the second part, we use the Europarl corpus and revisit the alignment procedure with which it has been prepared; we show that better SMT performance can be obtained using our alignment technique.

La quantité d'information disponible dans le domaine biomédical ne cesse d'augmenter. Pour que cette information soit facilement utilisable par les experts d'un domaine, il est nécessaire de l'extraire et de la structurer. Pour avoir des données structurées, il convient de détecter les relations existantes entre les entités dans les textes. Nos recherches se sont focalisées sur la question de l'extraction de relations complexes représentant des résultats expérimentaux, et sur la détection et la catégorisation de relations binaires entre des entités biomédicales. Nous nous sommes intéressée aux résultats expérimentaux présentés dans les articles scientifiques. Nous appelons résultat expérimental, un résultat quantitatif obtenu suite à une expérience et mis en relation avec les informations permettant de décrire cette expérience. Ces résultats sont importants pour les experts en biologie, par exemple pour faire de la modélisation. Dans le domaine de la physiologie rénale, une base de données a été créée pour centraliser ces résultats d'expérimentation, mais l'alimentation de la base est manuelle et de ce fait longue. Nous proposons une solution pour extraire automatiquement des articles scientifiques les connaissances pertinentes pour la base de données, c'est-à-dire des résultats expérimentaux que nous représentons par une relation n-aire. La méthode procède en deux étapes : extraction automatique des documents et proposition de celles-ci pour validation ou modification par l'expert via une interface. Nous avons également proposé une méthode à base d'apprentissage automatique pour l'extraction et la classification de relations binaires en domaine de spécialité. Nous nous sommes intéressée aux caractéristiques et variétés d'expressions des relations, et à la prise en compte de ces caractéristiques dans un système à base d'apprentissage. Nous avons étudié la prise en compte de la structure syntaxique de la phrase et la simplification de phrases dirigée pour la tâche d'extraction de relations. Nous avons en particulier développé une méthode de simplification à base d'apprentissage automatique, qui utilise en cascade plusieurs classifieurs. / The amount of available scientific literature is constantly growing. If the experts of a domain want to easily access this information, it must be extracted and structured. To obtain structured data, both entities and relations of the texts must be detected. Our research is about the problem of complex relation extraction which represent experimental results, and detection and classification of binary relations between biomedical entities. We are interested in experimental results presented in scientific papers. An experimental result is a quantitative result obtained by an experimentation and linked with information that describes this experimentation. These results are important for biology experts, for example for doing modelization. In the domain of renal physiology, a database was created to centralize these experimental results, but the base is manually populated, therefore the population takes a long time. We propose a solution to automatically extract relevant knowledge for the database from the scientific papers, that is experimental results which are represented by a n-ary relation. The method proceeds in two steps: automatic extraction from documents and proposal of information extracted for approval or modification by the experts via an interface. We also proposed a method based on machine learning for extraction and classification of binary relations in specialized domains. We focused on the variations of the expression of relations, and how to represent them in a machine learning system. We studied the way to take into account syntactic structure of the sentence and the sentence simplification guided by the task of relation extraction. In particular, we developed a simplification method based on machine learning, which uses a series of classifiers.

Este trabalho trata da organização de sintagmas nominais no armênio, revelando uma interação peculiar entre a expressão de definitude e a marcação morfológica de Caso e as conseqüências dessa relação para a organização estrutural desta língua. Mostra se que os sintagmas nominais são interpretados como definidos como resultado de atribuição de Caso estrutural, e que existe uma assimetria entre os Casos estruturais e os Casos inerentes quanto à atribuição de definitude. Como ponto de partida, discute-se o estatuto do sufixo n/y, chamado de artigo definido pela gramática tradicional do armênio. A investigação das propriedades morfossintáticas desse sufixo mostra que o mesmo é uma marca com características mistas, que atua na atribuição de definitude e Caso de uma maneira não atestada nas línguas naturais e questiona o recorte entre as funções de Caso e os meios de expressão de definitude. Baseando-nos nos trabalhos de Chomsky (1986b), Longobardi (1994) e Giusti (2002), propomos a reanálise do sufixo -n/y como uma marca de Caso estrutural, que transforma os sintagmas nominais em argumentos sintáticos, e é associada ao nível DP na estrutura frasal. Ademais, mostra-se que a ausência de marcação de Caso estrutural resulta numa série de restrições semântico-sintáticas nos sintagmas nominais (nus), a mais proeminente sendo o movimento desses sintagmas para uma posição antes do verbo, seguidos imediatamente pelo auxiliar. Isso leva a diferentes ordens superficiais para sintagmas marcados por Caso estrutural (SVO) e sintagmas nus (SOauxV). Tal evidência, junto com o quadro das características dos sintagmas nus no armênio, leva à análise dos mesmos como pseudo-incorporados, conforme proposto por Massam (2001) para o niueano, com a diferença de que o sintagma nu se adjunge à projeção funcional TP no armênio, sem passar pela operação de alçamento do predicado. Quanto à expressão de definitude nos Casos inerentes, mostramos que em contraste com os sintagmas nos Casos estruturais, que podem aparecer com ou sem marcação aberta de Caso e ter, respectivamente, leitura definida ou indefinida, os inerentes devem sempre carregar a morfologia casual e são ambíguos quanto à definitude. Nesse aspecto, analisamos as projeções nominais Genitivas e constatamos que, apesar da aparente semelhança superficial, as mesmas exibem propriedades distintas que correspondem a duas estruturas internas diferentes do sintagma nominal, viii podendo ser caracterizadas como duas classes distintas: o Genitivo Referencial, que aparece em Spec/DP e é interpretado como definido por se associar ao nível DP, e o Genitivo Modificador, que permanece no domínio do NP no percurso da derivação. As conclusões a que chegamos provam que mesmo sem possuir um artigo definido canônico, o armênio oferece evidências a favor da postulação do nível DP como universal, responsável pelas interpretações definidas dos sintagmas nominais. Nos Casos estruturais, a definitude vem da atribuição de Caso, enquanto no Genitivo (um exemplo de Caso inerente) vem da posição ocupada dentro do sintagma nominal. Por conseguinte, o presente trabalho traz uma contribuição teórica valiosa para a análise unificada das projeções nominais, além de auxiliar na elucidação de alguns assuntos empíricos controversos do armênio e abrir caminho para pesquisas futuras. / This thesis investigates the structural organization of noun phrases in Armenian, an Indo-European language with mixed properties, focusing on the interaction between Case and (in)definiteness. The main claim of the study is that, contrary to traditional view, Armenian has no (definite) article, and definiteness in this language is a result of structural Case marking on NPs. This claim has implications for the analysis of bare nominals as NPs that lack both Case and referential properties and are syntactically restricted to a peculiar configuration, resulting in different superficial orders for Case-marked (SVO) and bare noun phrases (SOauxV). Moreover, this analysis casts light on a rather intriguing question of how definiteness is expressed in inherent Cases. It is shown that, unlike structural Cases, which express a direct correlation between definiteness and Case, inherent Cases, more precisely Genitive NPs, are interpreted as (in)definite by associating themselves to distinct structural positions. The starting point of our discussion is the re-analysis of the suffix -n/y, traditionally classified as a definite article. Highlighting Case and (in)definiteness as two independent conditions on argumenthood (Chomsky (1986b), Longobardi (1994), Giusti (2002)) that are closely correlated in Armenian, we argue that this suffix is in fact a structural Case marker, which turns nominals into syntactic arguments, and is associated with DP level. Focusing on the morpho-syntactic behavior of bare nominals in Armenian, it is shown that in the absence of structural Case marking, their distribution is syntactically restricted to a position in which they appear to the left of the verb and must be adjacent to the auxiliary. This distribution is accounted for by adopting the pseudo-incorporation analysis of Massam (2001). We show that bare nouns in Armenian exhibit typical properties of pseudo-incorporated nominals, as lack of reference, number-neutrality, phrasal nature, among others. Turning our attention to Genitive constructions, which always appear with Case morphology, we analyze a number of properties that superficially distinguish two (main) types, which we propose to call Referential and Modifying Genitives. The difference between them is syntactic, as they have different structural representations: Spec/DP for Referential and NP domain for Modifying Genitive. x As a result, we conclude that there exists an asymmetry between inherent and structural Cases as to how they express definiteness. Moreover, we conclude that in spite of the fact that Armenian does not have canonical (definite) article, a DP level must be postulated for this language, as a projection responsible for the referentiality/definiteness of the noun phrases. Thus, this study contributes to the outgoing debates about the precise functions of D as universal category and provides a valuable theoretical contribution to the cross-linguistic investigations of nominal projections.

Apesar dos processos de recuperação e filtragem de informação sempre terem usado técnicas básicas de Processamento de Linguagem Natural (PLN) no suporte à estruturação de documentos, ainda são poucas as indicações sobre os avanços relacionados à utilização de técnicas mais sofisticadas de PLN que justifiquem o custo de sua utilização nestes processos, em comparação com as abordagens tradicionais. Este trabalho investiga algumas evidências que fundamentam a hipótese de que a aplicação de métodos que utilizam conhecimento linguístico é viável, demarcando importantes contribuições para o aumento de sua eficiência em adição aos métodos estatásticos tradicionais. É proposto um modelo de representação de texto fundamentado em sintagmas nominais, cuja representatividade de seus descritores é calculada utilizando-se o conceito de evidência, apoiado em métodos estatísticos. Filtros induzidos a partir desse modelo são utilizados para classificar os documentos recuperados analisando-se a relevância implícita no perfil do usuário. O aumento da precisão (e, portanto, da eficácia) em sistemas de Recuperação de Informação, conseqüência da pós-filtragem seletiva de informações, demonstra uma clara evidência de como o uso de técnicas de PLN pode auxiliar a categorização de textos, abrindo reais possibilidades para o aprimoramento do modelo apresentado / Although Information Retrieval and Filtering tasks have always used basic Natural Language Processing (NLP) techniques for supporting document structuring, there is still space for more sophisticated NLP techniques which justify their cost when compared to the traditional approaches. This research aims to investigate some evidences that justify the hypothesis on which the use of linguistic-based methods is feasible and can bring on relevant contributions to this area. In this work noun phrases of a text are used as descriptors whose evidence is calculated by statistical methods. Filters are then induced to classify the retrieved documents by measuring their implicit relevance presupposed by an user profile. The increase of precision (efficacy) in IR systems as a consequence of the use of NLP techniques for text classification in the filtering task is an evidence of how this approach can be further explored

L'expression « éducation populaire » connaît en France une nouvelle fortune depuis les années 1990. La recherche vise à éclaircir le sens et les causes de ce retour en grâce discursif. On définit la séquence « éducation populaire » comme une formule, au sens de l'analyse du discours, en lien avec la notion de catégorie. L'étude du retour contemporain de celle-ci impose un long détour par son histoire. Celle-ci se décompose en deux cycles complet constitués de phases d'émergence, de consécration et de déclin autour d'un usage de la formule comme quasi-catégorie : sous-catégorie de l'Instruction publique entre la Révolution française et les années 1930, puis catégorie détachée de l'École mais associée à des formules concurrentes et bientôt reléguées par elles au rang d'ancêtre mythique. La période contemporaine se présente comme l'émergence d’un usage détaché de l’animation socioculturelle et orientée vers la formation militante et la repolitisation des politiques culturelles ; ce nouvel usage, qui demeure toutefois en concurrence avec une remobilisation du secteur Jeunesse et Éducation populaire, réintroduit en outre les pratiques d’origine scolaires que ce dernier avait écartées. / The set phrase "éducation populaire" has been especially successful in French public discourses since the 1990s. We intend to analyze this lexical comeback. The past life of the phrase can be divided in two cycles, each of them composed of successive phases of emergence, consecration and decline, and revolving around an interpretation of the phrase as a quasi-category. It starts as a subcategory of "Instruction publique" from the French Revolution to the 1930s, then becomes a category detachedfrom schooling but linked with competing phrases, and is soon discarded by these ones as a mythical ancestor. The last years witness a new, yet uncertain phase of emergence which defines "éducation populaire" as a form of radical political education or as a repoliticization of cultural policies. This new use, however, is competing with the remobilization of traditional movements. It also reintroduces the school-rooted practices which had been previously discarded.