980 resultados para International conferences


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The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

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Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

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Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

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Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.

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Introduction: The built environment is increasingly recognised as being associated with health outcomes. Relationships between the built environment and health differ among age groups, especially between children and adults, but also between younger, mid-age and older adults. Yet few address differences across life stage groups within a single population study. Moreover, existing research mostly focuses on physical activity behaviours, with few studying objective clinical and mental health outcomes. The Life Course Built Environment and Health (LCBEH) project explores the impact of the built environment on self-reported and objectively measured health outcomes in a random sample of people across the life course. Methods and analysis: This cross-sectional data linkage study involves 15 954 children (0–15 years), young adults (16–24 years), adults (25–64 years) and older adults (65+years) from the Perth metropolitan region who completed the Health and Wellbeing Surveillance System survey administered by the Department of Health of Western Australia from 2003 to 2009. Survey data were linked to Western Australia's (WA) Hospital Morbidity Database System (hospital admission) and Mental Health Information System (mental health system outpatient) data. Participants’ residential address was geocoded and features of their ‘neighbourhood’ were measured using Geographic Information Systems software. Associations between the built environment and self-reported and clinical health outcomes will be explored across varying geographic scales and life stages. Ethics and dissemination: The University of Western Australia's Human Research Ethics Committee and the Department of Health of Western Australia approved the study protocol (#2010/1). Findings will be published in peer-reviewed journals and presented at local, national and international conferences, thus contributing to the evidence base informing the design of healthy neighbourhoods for all residents.

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This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.

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INTRODUCTION Influenza vaccination in pregnancy is recommended for all women in Australia, particularly those who will be in their second or third trimester during the influenza season. However, there has been no systematic monitoring of influenza vaccine uptake among pregnant women in Australia. Evidence is emerging of benefit to the infant with respect to preventing influenza infection in the first 6 months of life. The FluMum study aims to systematically monitor influenza vaccine uptake during pregnancy in Australia and determine the effectiveness of maternal vaccination in preventing laboratory-confirmed influenza in their offspring up to 6 months of age. METHODS AND ANALYSIS A prospective cohort study of 10 106 mother-infant pairs recruited between 38 weeks gestation and 55 days postdelivery in six Australian capital cities. Detailed maternal and infant information is collected at enrolment, including influenza illness and vaccination history with a follow-up data collection time point at infant age 6 months. The primary outcome is laboratory-confirmed influenza in the infant. Case ascertainment occurs through searches of Australian notifiable diseases data sets once the infant turns 6 months of age (with parental consent). The primary analysis involves calculating vaccine effectiveness against laboratory-confirmed influenza by comparing the incidence of influenza in infants of vaccinated mothers to the incidence in infants of unvaccinated mothers. Secondary analyses include annual and pooled estimates of the proportion of mothers vaccinated during pregnancy, the effectiveness of maternal vaccination in preventing hospitalisation for acute respiratory illness and modelling to assess the determinants of vaccination. ETHICS AND DISSEMINATION The study was approved by all institutional Human Research Ethics Committees responsible for participating sites. Study findings will be published in peer review journals and presented at national and international conferences. TRIAL REGISTRATION NUMBER The study is registered with the Australia and New Zealand Clinical Trials Registry (ANZCTR) number: 12612000175875.

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Recent 'Global Burden of Disease' studies have provided quantitative evidence of the significant role air pollution plays as a human health risk factor (Lim et al., The Lancet, 380: 2224–2260, 2012). Tobacco smoke, including second hand smoke, household air pollution from solid fuels and ambient particulate matter are among the top risks, leading to lower life expectancy around the world. Indoor air constitutes an environment particularly rich in different types of pollutants, originating from indoor sources, as well as penetrating from outdoors, mixing, interacting or growing (when considering microbes) under the protective enclosure of the building envelope. Therefore, it is not a simple task to follow the dynamics of the processes occurring there, or to quantify the outcomes of the processes in terms of pollutant concentrations and other characteristics. This is further complicated by limitations such as building access for the purpose of air quality monitoring, or the instrumentation which can be used indoors, because of their possible interference with the occupants comfort (due to their large size, noise generated or amount of air drawn). European studies apportioned contributions of indoor versus outdoor sources of indoor air contaminants in 26 European countries and quantified IAQ associated DALYs (Disability-Adjusted Life Years) in those countries (Jantunen et al., Promoting actions for healthy indoor air (IAIAQ), European Commission Directorate General for Health and Consumers, Luxembourg, 2011). At the same time, there has been an increase in research efforts around the world to better understand the sources, composition, dynamics and impacts of indoor air pollution. Particular focus has been directed towards the contemporary sources, novel pollutants and new detection methods. The importance of exposure assessment and personal exposure, the majority of which occurs in various indoor micro¬environments, has also been realized. Overall, this emerging knowledge has been providing input for global assessments of indoor environments, the impact of indoor pollutants and their science based management and control. It was a major outcome of recent international conferences that interdisciplinarity and especially a better colla¬boration between exposure and indoor sciences would be of high benefit for the health related evaluation of environmental stress factors and pollutants. A very good example is the combination of biomonitoring and indoor air, particle and dust analysis to study the exposure routes of semi volatile organic compounds (SVOCs). We have adopted the idea of combining the forces of exposure and indoor sciences for this Special Issue, identified new and challenging topics and have attracted colleagues who are top researchers in their field to provide their inputs. The Special Issue includes papers, which collectively present advances in current research topics and in our view, build the bridge between indoor and exposure sciences.

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Essa dissertação tem por objeto de estudo a política de saúde em geral, recortada a partir do desenvolvimento das conferências internacionais de promoção da saúde. Observando a inflexão ideológica que os próprios conceitos de saúde e promoção sofrem. Há uma ação operada pelo capital através dos organismos internacionais de esvaziamento do conteúdo progressista para que se agregue valores de mercado à esse setor, e sua virtual transformação em mercadoria promotora de lucros em substituição a sua concretização como direito inalienável do ser humano. Com recorte no município de Niterói, município que fora berço do movimento e de experiências da Reforma Sanitário, foi possível observar a repercussão desse processo de inflexão ideológica operada pelo capital no campo da saúde.