904 resultados para Romance languages -- To 1500 -- Word order -- Congresses
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These five manuals show you how to use a range of Word 2010 features and the University's non-compulsory thesis template to produce your thesis. It shows how to save time and create a clearly structured & consistent looking document.
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These five manuals show you how to use a range of Word 2011 features and the University's non-compulsory thesis template to produce your thesis. It shows how to save time and create a clearly structured & consistent looking document.
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These five manuals show you how to use a range of Word 2010 features and the University's non-compulsory thesis template to produce your thesis. It shows how to save time and create a clearly structured & consistent looking document.
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Resumen tomado del autor. Resumen también en francés e inglés
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En los últimos años se ha experimentado un rápido crecimiento del número de niños que en edades más jóvenes han aprendido lenguas extranjeras, por ello, este texto ofrece a los profesores y formadores un marco teórico para estructurar las ideas sobre el aprendizaje del lenguaje pos los niños. Se citan ejemplos de aulas en Europa y Asia, en las que se trabaja con jóvenes estudiantes de inglés.También, proporciona consejos prácticos sobre cómo analizar y evaluar las actividades del aula y sobre el uso y desarrollo del lenguaje.
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Monogr??fico con el t??tulo: 'Nuevas perspectivas en la secci??n de idiomas de la Prueba de Acceso a la Universidad'. Resumen basado en el de la publicaci??n
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This paper studies the effectiveness of the recorded books and teaching method developed by Dr. Marie Carbo in the aural habilitation of pre-lingual deaf children with cochlear implants.
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Word sense disambiguation is the task of determining which sense of a word is intended from its context. Previous methods have found the lack of training data and the restrictiveness of dictionaries' choices of senses to be major stumbling blocks. A robust novel algorithm is presented that uses multiple dictionaries, the Internet, clustering and triangulation to attempt to discern the most useful senses of a given word and learn how they can be disambiguated. The algorithm is explained, and some promising sample results are given.
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While eye movements have been used widely to investigate how skilled adult readers process written language, relatively little research has used this methodology with children. This is unfortunate as, as we discuss here, eye-movement studies have significant potential to inform our understanding of children’s reading development. We consider some of the empirical and theoretical issues that arise when using this methodology with children, illustrating our points with data from an experiment examining word frequency effects in 8-year-old children’s sentence reading. Children showed significantly longer gaze durations to low than high-frequency words, demonstrating that linguistic characteristics of text drive children’s eye movements as they read. We discuss these findings within the broader context of how eye-movement studies can inform our understanding of children’s reading, and can assist with the development of appropriately targeted interventions to support children as they learn to read.
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Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)