814 resultados para Topic representation


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The representation of age groups is becoming an increasingly discussed topic in Swiss politics. In this study, we explore inequalities in the descriptive and substantive representation of various age groups and find that despite important disparities in descriptive representation, the policy preferences of various age groups are relatively equally represented in the lower house of the Swiss parliament. Our analysis thus suggests that even if it is gaining visibility, the age cleavage is not central for parliamentary representation in Switzerland.

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This article attempts to assess the implications and the own character of the crisis of representation in Mexico. Once the topic framed and the long-term dynamics of Mexican political elites presented, this paper will attempt to understand why, despite the pluralization of the party system, there remain many questions about the truly democratic nature of the Mexican political system.

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Drawing on attitude theory, this study investigates the drivers of employees' expression of favorable opinions about their workplace. Despite its theoretical and managerial importance, the marketing literature largely ignores the topic. This study advances prior research by developing, and empirically testing, a conceptual framework of the relationship between workgroup support and favorable external representation of the workplace, mediated by emotional responses to this support. The present research investigates four new relationships: between workgroup support and emotional exhaustion, workgroup support and organizational commitment, workgroup support and job satisfaction, and emotional exhaustion and external representation of the workplace. Based on a sample of over 700 frontline service employees, this study finds that workgroup support affects favorable external representation of the workplace through various emotional responses (i.e., emotional exhaustion, organizational commitment and job satisfaction). In addition, the results identify employees' organizational commitment as the most important determinant of favorable external representation of the workplace, followed by job satisfaction and reduced emotional exhaustion. These results suggest that companies should develop practices that encourage workgroup support and organizational commitment to achieve favorable external representation of the workplace.

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The research topic of this paper is focused on the analysis of how trade associations perceive lobbying in Brussels and in Brasília. The analysis will be centered on business associations located in Brasília and Brussels as the two core centers of decision-making and as an attraction for the lobbying practice. The underlying principles behind the comparison between Brussels and Brasilia are two. Firstof all because the European Union and Brazil have maintained diplomatic relations since 1960. Through these relations they have built up close historical, cultural, economic and political ties. Their bilateral political relations culminated in 2007 with the establishment of a Strategic Partnership (EEAS website,n.d.). Over the years, Brazil has become a key interlocutor for the EU and it is the most important market for the EU in Latin America (European Commission, 2007). Taking into account the relations between EU and Brazil, this research could contribute to the reciprocal knowledge about the perception of lobby in the respective systems and the importance of the non-market strategy when conducting business. Second both EU and Brazilian systems have a multi-level governance structure: 28 Member States in the EU and 26 Member States in Brazil; in both systems there are three main institutions targeted by lobbying practice. The objective is to compare how differences in the institutional environments affect the perception and practice of lobbying, where institutions are defined as ‘‘regulative, normative, and cognitive structures and activities that provide stability and meaning to social behavior’’ (Peng et al., 2009). Brussels, the self-proclaimed "Capital of Europe”, is the headquarters of the European Union and has one of the highest concentrations of political power in the world. Four of the seven Institutions of the European Union are based in Brussels: the European Parliament, the European Council, the Council and the European Commission (EU website, n.d.). As the power of the EU institutions has grown, Brussels has become a magnet for lobbyists, with the latest estimates ranging from between 15,000 and 30,000 professionals representing companies, industry sectors, farmers, civil society groups, unions etc. (Burson Marsteller, 2013). Brasília is the capital of Brazil and the seat of government of the Federal District and the three branches of the federal government of Brazilian legislative, executive and judiciary. The 4 city also hosts 124 foreign embassies. The presence of the formal representations of companies and trade associations in Brasília is very limited, but the governmental interests remain there and the professionals dealing with government affairs commute there. In the European Union, Brussels has established a Transparency Register that allows the interactions between the European institutions and citizen’s associations, NGOs, businesses, trade and professional organizations, trade unions and think tanks. The register provides citizens with a direct and single access to information about who is engaged in This process is important for the quality of democracy, and for its capacity to deliver adequate policies, matching activities aimed at influencing the EU decision-making process, which interests are being pursued and what level of resources are invested in these activities (Celgene, n.d). It offers a single code of conduct, binding all organizations and self-employed individuals who accept to “play by the rules” in full respect of ethical principles (EC website, n.d). A complaints and sanctions mechanism ensures the enforcement of the rules and addresses suspected breaches of the code. In Brazil, there is no specific legislation regulating lobbying. The National Congress is currently discussing dozens of bills that address regulation of lobbying and the action of interest groups (De Aragão, 2012), but none of them has been enacted for the moment. This work will focus on class lobbying (Oliveira, 2004), which refers to the performance of the federation of national labour or industrial unions, like CNI (National Industry Confederation) in Brazil and the European Banking Federation (EBF) in Brussels. Their performance aims to influence the Executive and Legislative branches in order to defend the interests of their affiliates. When representing unions and federations, class entities cover a wide range of different and, more often than not, conflicting interests. That is why they are limited to defending the consensual and majority interest of their affiliates (Oliveira, 2004). The basic assumption of this work is that institutions matter (Peng et al, 2009) and that the trade associations and their affiliates, when doing business, have to take into account the institutional and regulatory framework where they do business.

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Characteristics of speech, especially figures of speech, are used by specific communities or domains, and, in this way, reflect their identities through their choice of vocabulary. This topic should be an object of study in the context of knowledge representation once it deals with different contexts of production of documents. This study aims to explore the dimensions of the concepts of euphemism, dysphemism, and orthophemism, focusing on the latter with the goal of extracting a concept which can be included in discussions about subject analysis and indexing. Euphemism is used as an alternative to a non-preferred expression or as an alternative to an offensive attribution-to avoid potential offense taken by the listener or by other persons, for instance, pass away. Dysphemism, on the other hand, is used by speakers to talk about people and things that frustrate and annoy them-their choice of language indicates disapproval and the topic is therefore denigrated, humiliated, or degraded, for instance, kick the bucket. While euphemism tries to make something sound better, dysphemism tries to make something sound worse. Orthophemism (Allan and Burridge 2006) is also used as an alternative to expressions, but it is a preferred, formal, and direct language of expression when representing an object or a situation, for instance, die. This paper suggests that the comprehension and use of such concepts could support the following issues: possible contributions from linguistics and terminology to subject analysis as demonstrated by Talamo et al. (1992); decrease of polysemy and ambiguity of terms used to represent certain topics of documents; and construction and evaluation of indexing languages. The concept of orthophemism can also serves to support associative relationships in the context of subject analysis, indexing, and even information retrieval related to more specific requests.

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Thesis (Master's)--University of Washington, 2016-06

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In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

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This research was conducted at the Space Research and Technology Centre o the European Space Agency at Noordvijk in the Netherlands. ESA is an international organisation that brings together a range of scientists, engineers and managers from 14 European member states. The motivation for the work was to enable decision-makers, in a culturally and technologically diverse organisation, to share information for the purpose of making decisions that are well informed about the risk-related aspects of the situations they seek to address. The research examined the use of decision support system DSS) technology to facilitate decision-making of this type. This involved identifying the technology available and its application to risk management. Decision-making is a complex activity that does not lend itself to exact measurement or precise understanding at a detailed level. In view of this, a prototype DSS was developed through which to understand the practical issues to be accommodated and to evaluate alternative approaches to supporting decision-making of this type. The problem of measuring the effect upon the quality of decisions has been approached through expert evaluation of the software developed. The practical orientation of this work was informed by a review of the relevant literature in decision-making, risk management, decision support and information technology. Communication and information technology unite the major the,es of this work. This allows correlation of the interests of the research with European public policy. The principles of communication were also considered in the topic of information visualisation - this emerging technology exploits flexible modes of human computer interaction (HCI) to improve the cognition of complex data. Risk management is itself an area characterised by complexity and risk visualisation is advocated for application in this field of endeavour. The thesis provides recommendations for future work in the fields of decision=making, DSS technology and risk management.

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Short text messages a.k.a Microposts (e.g. Tweets) have proven to be an effective channel for revealing information about trends and events, ranging from those related to Disaster (e.g. hurricane Sandy) to those related to Violence (e.g. Egyptian revolution). Being informed about such events as they occur could be extremely important to authorities and emergency professionals by allowing such parties to immediately respond. In this work we study the problem of topic classification (TC) of Microposts, which aims to automatically classify short messages based on the subject(s) discussed in them. The accurate TC of Microposts however is a challenging task since the limited number of tokens in a post often implies a lack of sufficient contextual information. In order to provide contextual information to Microposts, we present and evaluate several graph structures surrounding concepts present in linked knowledge sources (KSs). Traditional TC techniques enrich the content of Microposts with features extracted only from the Microposts content. In contrast our approach relies on the generation of different weighted semantic meta-graphs extracted from linked KSs. We introduce a new semantic graph, called category meta-graph. This novel meta-graph provides a more fine grained categorisation of concepts providing a set of novel semantic features. Our findings show that such category meta-graph features effectively improve the performance of a topic classifier of Microposts. Furthermore our goal is also to understand which semantic feature contributes to the performance of a topic classifier. For this reason we propose an approach for automatic estimation of accuracy loss of a topic classifier on new, unseen Microposts. We introduce and evaluate novel topic similarity measures, which capture the similarity between the KS documents and Microposts at a conceptual level, considering the enriched representation of these documents. Extensive evaluation in the context of Emergency Response (ER) and Violence Detection (VD) revealed that our approach outperforms previous approaches using single KS without linked data and Twitter data only up to 31.4% in terms of F1 measure. Our main findings indicate that the new category graph contains useful information for TC and achieves comparable results to previously used semantic graphs. Furthermore our results also indicate that the accuracy of a topic classifier can be accurately predicted using the enhanced text representation, outperforming previous approaches considering content-based similarity measures. © 2014 Elsevier B.V. All rights reserved.

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Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.

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Lecture on the topic of the representation of violence in motion pictures, presented at Books & Books Coral Gables on January 29, 2013.

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Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

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The objective of the present research is to describe and explain populist actors and populism as a concept and their representation on social and legacy media during the 2019 EU elections in Finland, Italy and The Netherlands. This research tackles the topic of European populism in the context of political communication and its relation to both the legacy and digital media within the hybrid media system. Departing from the consideration that populism and populist rhetoric are challenging concepts to define, I suggest that they should be addressed and analyzed through the usage of a combination of methods and theoretical perspectives, namely Communication Studies, Corpus Linguistics, Political theory, Rhetoric and Corpus-Assisted Discourse Studies. This thesis considers data of different provenance. On the one hand, for the Legacy media part, newspapers articles were collected in the three countries under study from the 1st until the 31st of May 2019. Each country’s legacy system is represented by three different quality papers and the articles were collected according to a selection of keywords (European Union Elections and Populism in each of the three languages). On the other hand, the Digital media data takes into consideration Twitter tweets collected during the same timeframe based on particular country-specific hashtags and tweets by identified populist actors. In order to meet the objective of this study, three research questions are posed and the analysis leading to the results are exhaustively presented and further discussed. The results of this research provide valuable and novel insights on how populism as a theme and a concept is being portrayed in the context of the European elections both in legacy and digital media and political communication in general.

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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Universidade Estadual de Campinas . Faculdade de Educação Física