939 resultados para Open Information Extraction
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The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.
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Massive Open Online Courses (MOOC) are gaining prominence in transversal teaching-learning strategies. However, there are many issues still debated, namely assessment, recognized largely as a cornerstone in Education. The large number of students involved requires a redefinition of strategies that often use approaches based on tasks or challenging projects. In these conditions and due to this approach, assessment is made through peer-reviewed assignments and quizzes online. The peer-reviewed assignments are often based upon sample answers or topics, which guide the student in the task of evaluating peers. This chapter analyzes the grading and evaluation in MOOCs, especially in science and engineering courses, within the context of education and grading methodologies and discusses possible perspectives to pursue grading quality in massive e-learning courses.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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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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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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O sector do turismo é uma área francamente em crescimento em Portugal e que tem desenvolvido a sua divulgação e estratégia de marketing. Contudo, apenas se prende com indicadores de desempenho e de oferta instalada (número de quartos, hotéis, voos, estadias), deixando os indicadores estatísticos em segundo plano. De acordo com o “ Travel & tourism Competitiveness Report 2013”, do World Economic Forum, classifica Portugal em 72º lugar no que respeita à qualidade e cobertura da informação estatística, disponível para o sector do Turismo. Refira-se que Espanha ocupa o 3º lugar. Uma estratégia de mercado, sem base analítica, que sustente um quadro de orientações específico e objetivo, com relevante conhecimento dos mercados alvo, dificilmente é compreensível ou até mesmo materializável. A implementação de uma estrutura de Business Intelligence que permita a realização de um levantamento e tratamento de dados que possibilite relacionar e sustentar os resultados obtidos no sector do turismo revela-se fundamental e crucial, para que sejam criadas estratégias de mercado. Essas estratégias são realizadas a partir da informação dos turistas que nos visitam, e dos potenciais turistas, para que possam ser cativados no futuro. A análise das características e dos padrões comportamentais dos turistas permite definir perfis distintos e assim detetar as tendências de mercado, de forma a promover a oferta dos produtos e serviços mais adequados. O conhecimento obtido permite, por um lado criar e disponibilizar os produtos mais atrativos para oferecer aos turistas e por outro informá-los, de uma forma direcionada, da existência desses produtos. Assim, a associação de uma recomendação personalizada que, com base no conhecimento de perfis do turista proceda ao aconselhamento dos melhores produtos, revela-se como uma ferramenta essencial na captação e expansão de mercado.
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É possível assistir nos dias de hoje, a um processo tecnológico evolutivo acentuado por toda a parte do globo. No caso das empresas, quer as pequenas, médias ou de grandes dimensões, estão cada vez mais dependentes dos sistemas informatizados para realizar os seus processos de negócio, e consequentemente à geração de informação referente aos negócios e onde, muitas das vezes, os dados não têm qualquer relacionamento entre si. A maioria dos sistemas convencionais informáticos não são projetados para gerir e armazenar informações estratégicas, impossibilitando assim que esta sirva de apoio como recurso estratégico. Portanto, as decisões são tomadas com base na experiência dos administradores, quando poderiam serem baseadas em factos históricos armazenados pelos diversos sistemas. Genericamente, as organizações possuem muitos dados, mas na maioria dos casos extraem pouca informação, o que é um problema em termos de mercados competitivos. Como as organizações procuram evoluir e superar a concorrência nas tomadas de decisão, surge neste contexto o termo Business Intelligence(BI). A GisGeo Information Systems é uma empresa que desenvolve software baseado em SIG (sistemas de informação geográfica) recorrendo a uma filosofia de ferramentas open-source. O seu principal produto baseia-se na localização geográfica dos vários tipos de viaturas, na recolha de dados, e consequentemente a sua análise (quilómetros percorridos, duração de uma viagem entre dois pontos definidos, consumo de combustível, etc.). Neste âmbito surge o tema deste projeto que tem objetivo de dar uma perspetiva diferente aos dados existentes, cruzando os conceitos BI com o sistema implementado na empresa de acordo com a sua filosofia. Neste projeto são abordados alguns dos conceitos mais importantes adjacentes a BI como, por exemplo, modelo dimensional, data Warehouse, o processo ETL e OLAP, seguindo a metodologia de Ralph Kimball. São também estudadas algumas das principais ferramentas open-source existentes no mercado, assim como quais as suas vantagens/desvantagens relativamente entre elas. Em conclusão, é então apresentada a solução desenvolvida de acordo com os critérios enumerados pela empresa como prova de conceito da aplicabilidade da área Business Intelligence ao ramo de Sistemas de informação Geográfica (SIG), recorrendo a uma ferramenta open-source que suporte visualização dos dados através de dashboards.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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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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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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The present article is based on the report for the Doctoral Conference of the PhD programme in Technology Assessment, held at FCT-UNL Campus, Monte de Caparica, July 9th, 2012. The PhD thesis has the supervision of Prof. Cristina Sousa (ISCTE-IUL), and co-supervision of Prof. José Cardoso e Cunha (FCT-UNL).
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African elections often reveal low levels of political accountability. We assess different forms of voter education during an election in Mozambique. Three interventions providing information to voters and calling for their electoral participation were randomized; an SMS-based information campaign, an SMS hotline for electoral misconduct, and the distribution of a free newspaper. To measure impact, we look at official electoral results, reports by electoral observers, behavioral and survey data. We find positive effects of all treatments on voter turnout. We observe that the distribution of the newspaper led to more accountability-based participation and to a decrease in electoral problems.
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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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The extraction of relevant terms from texts is an extensively researched task in Text- Mining. Relevant terms have been applied in areas such as Information Retrieval or document clustering and classification. However, relevance has a rather fuzzy nature since the classification of some terms as relevant or not relevant is not consensual. For instance, while words such as "president" and "republic" are generally considered relevant by human evaluators, and words like "the" and "or" are not, terms such as "read" and "finish" gather no consensus about their semantic and informativeness. Concepts, on the other hand, have a less fuzzy nature. Therefore, instead of deciding on the relevance of a term during the extraction phase, as most extractors do, I propose to first extract, from texts, what I have called generic concepts (all concepts) and postpone the decision about relevance for downstream applications, accordingly to their needs. For instance, a keyword extractor may assume that the most relevant keywords are the most frequent concepts on the documents. Moreover, most statistical extractors are incapable of extracting single-word and multi-word expressions using the same methodology. These factors led to the development of the ConceptExtractor, a statistical and language-independent methodology which is explained in Part I of this thesis. In Part II, I will show that the automatic extraction of concepts has great applicability. For instance, for the extraction of keywords from documents, using the Tf-Idf metric only on concepts yields better results than using Tf-Idf without concepts, specially for multi-words. In addition, since concepts can be semantically related to other concepts, this allows us to build implicit document descriptors. These applications led to published work. Finally, I will present some work that, although not published yet, is briefly discussed in this document.
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The particular characteristics and affordances of technologies play a significant role in human experience by defining the realm of possibilities available to individuals and societies. Some technological configurations, such as the Internet, facilitate peer-to-peer communication and participatory behaviors. Others, like television broadcasting, tend to encourage centralization of creative processes and unidirectional communication. In other instances still, the affordances of technologies can be further constrained by social practices. That is the case, for example, of radio which, although technically allowing peer-to-peer communication, has effectively been converted into a broadcast medium through the legislation of the airwaves. How technologies acquire particular properties, meanings and uses, and who is involved in those decisions are the broader questions explored here. Although a long line of thought maintains that technologies evolve according to the logic of scientific rationality, recent studies demonstrated that technologies are, in fact, primarily shaped by social forces in specific historical contexts. In this view, adopted here, there is no one best way to design a technological artifact or system; the selection between alternative designs—which determine the affordances of each technology—is made by social actors according to their particular values, assumptions and goals. Thus, the arrangement of technical elements in any technological artifact is configured to conform to the views and interests of those involved in its development. Understanding how technologies assume particular shapes, who is involved in these decisions and how, in turn, they propitiate particular behaviors and modes of organization but not others, requires understanding the contexts in which they are developed. It is argued here that, throughout the last century, two distinct approaches to the development and dissemination of technologies have coexisted. In each of these models, based on fundamentally different ethoi, technologies are developed through different processes and by different participants—and therefore tend to assume different shapes and offer different possibilities. In the first of these approaches, the dominant model in Western societies, technologies are typically developed by firms, manufactured in large factories, and subsequently disseminated to the rest of the population for consumption. In this centralized model, the role of users is limited to selecting from the alternatives presented by professional producers. Thus, according to this approach, the technologies that are now so deeply woven into human experience, are primarily shaped by a relatively small number of producers. In recent years, however, a group of three interconnected interest groups—the makers, hackerspaces, and open source hardware communities—have increasingly challenged this dominant model by enacting an alternative approach in which technologies are both individually transformed and collectively shaped. Through a in-depth analysis of these phenomena, their practices and ethos, it is argued here that the distributed approach practiced by these communities offers a practical path towards a democratization of the technosphere by: 1) demystifying technologies, 2) providing the public with the tools and knowledge necessary to understand and shape technologies, and 3) encouraging citizen participation in the development of technologies.