865 resultados para Semantic TuCSoN, eHealth


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In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

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The semantic localization problem in robotics consists in determining the place where a robot is located by means of semantic categories. The problem is usually addressed as a supervised classification process, where input data correspond to robot perceptions while classes to semantic categories, like kitchen or corridor. In this paper we propose a framework, implemented in the PCL library, which provides a set of valuable tools to easily develop and evaluate semantic localization systems. The implementation includes the generation of 3D global descriptors following a Bag-of-Words approach. This allows the generation of fixed-dimensionality descriptors from any type of keypoint detector and feature extractor combinations. The framework has been designed, structured and implemented to be easily extended with different keypoint detectors, feature extractors as well as classification models. The proposed framework has also been used to evaluate the performance of a set of already implemented descriptors, when used as input for a specific semantic localization system. The obtained results are discussed paying special attention to the internal parameters of the BoW descriptor generation process. Moreover, we also review the combination of some keypoint detectors with different 3D descriptor generation techniques.

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The reprise evidential conditional (REC) is nowadays not very usual in Catalan: it is restricted to journalistic language and to some very formal genres (such as academic or legal language), it is not present in spontaneous discourse. On the one hand, it has been described among the rather new modality values of the conditional. On the other, the normative tradition tended to reject it for being a gallicism, or to describe it as an unsuitable neologism. Thanks to the extraction from text corpora, we surprisingly find this REC in Catalan from the beginning of the fourteenth century to the contemporary age, with semantic and pragmatic nuances and different evidence of grammaticalization. Due to the current interest in evidentiality, the REC has been widely studied in French, Italian and Portuguese, focusing mainly on its contemporary uses and not so intensively on the diachronic process that could explain the origin of this value. In line with this research, that we initiated studying the epistemic and evidential future in Catalan, our aim is to describe: a) the pragmatic context that could have been the initial point of the REC in the thirteenth century, before we find indisputable attestations of this use; b) the path of semantic change followed by the conditional from a ‘future in the past’ tense to the acquisition of epistemic and evidential values; and c) the role played by invited inferences, subjectification and intersubjectification in this change.

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Presentation of the volume.

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In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly.

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Especially in functional-typological linguistics, semantic roles have been studied thoroughly, because they constitute a good starting point for any study on argument marking due to their semantically defined nature. However, the very concept of semantic roles is far from being without problems, and there is still no consensus on how the roles are best defined. In this volume, the notion will be discussed from novel perspectives with the aim of providing new insights into our understanding of semantic roles. Two of the papers deal with semantic role clusters, one with semantic roles in verbless constructions, one with diachrony of semantic roles and two with individual semantic roles that have not been studied in too much detail in previous studies. The book may not offer answers to all questions the readers may have, but at least it raises interesting further questions relevant to arriving at a better understanding of semantic roles.

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Bibliography: p. 87.

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Includes bibliography.

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Bibliography: p. 75.

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Sponsored by Inventory Working Group, Society of American Foresters; School of Renewable Natural Resources, University of Arizona; Forest Service, U.S. Dept. of Agriculture; Bureau of Land Management, U.S. Dept. of the Interior; and Renewable Natural Resources Foundation.

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Research on semantic processing focused mainly on isolated units in language, which does not reflect the complexity of language. In order to understand how semantic information is processed in a wider context, the first goal of this thesis was to determine whether Swedish pre-school children are able to comprehend semantic context and if that context is semantically built up over time. The second goal was to investigate how the brain distributes attentional resources by means of brain activation amplitude and processing type. Swedish preschool children were tested in a dichotic listening task with longer children’s narratives. The development of event-related potential N400 component and its amplitude were used to investigate both goals. The decrease of the N400 in the attended and unattended channel indicated semantic comprehension and that semantic context was built up over time. The attended stimulus received more resources, processed the stimuli in more of a top-down manner and displayed prominent N400 amplitude in contrast to the unattended stimulus. The N400 and the late positivity were more complex than expected since endings of utterances longer than nine words were not accounted for. More research on wider linguistic context is needed in order to understand how the human brain comprehends natural language.