27 resultados para Query expansion, Text mining, Information retrieval, Chinese IR


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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática

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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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From a narratological perspective, this paper aims to address the theoretical issues concerning the functioning of the so called «narrative bifurcation» in data presentation and information retrieval. Its use in cyberspace calls for a reassessment as a storytelling device. Films have shown its fundamental role for the creation of suspense. Interactive fiction and games have unveiled the possibility of plots with multiple choices, giving continuity to cinema split-screen experiences. Using practical examples, this paper will show how this storytelling tool returns to its primitive form and ends up by conditioning cloud computing interface design.

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This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.

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Fado was listed as UNESCO Intangible Cultural Heritage in 2011. This dissertation describes a theoretical model, as well as an automatic system, able to generate instrumental music based on the musics and vocal sounds typically associated with fado’s practice. A description of the phenomenon of fado, its musics and vocal sounds, based on ethnographic, historical sources and empirical data is presented. The data includes the creation of a digital corpus, of musical transcriptions, identified as fado, and statistical analysis via music information retrieval techniques. The second part consists in the formulation of a theory and the coding of a symbolic model, as a proof of concept, for the automatic generation of instrumental music based on the one in the corpus.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de Construção

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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.