23 resultados para Open Information Extraction


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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.

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Currently the world swiftly adapts to visual communication. Online services like YouTube and Vine show that video is no longer the domain of broadcast television only. Video is used for different purposes like entertainment, information, education or communication. The rapid growth of today’s video archives with sparsely available editorial data creates a big problem of its retrieval. The humans see a video like a complex interplay of cognitive concepts. As a result there is a need to build a bridge between numeric values and semantic concepts. This establishes a connection that will facilitate videos’ retrieval by humans. The critical aspect of this bridge is video annotation. The process could be done manually or automatically. Manual annotation is very tedious, subjective and expensive. Therefore automatic annotation is being actively studied. In this thesis we focus on the multimedia content automatic annotation. Namely the use of analysis techniques for information retrieval allowing to automatically extract metadata from video in a videomail system. Furthermore the identification of text, people, actions, spaces, objects, including animals and plants. Hence it will be possible to align multimedia content with the text presented in the email message and the creation of applications for semantic video database indexing and retrieving.