1,721,055 research outputs found

    A Survey of Sentimental Analysis Methods on COVID-19 Research

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    In this era of social media, people share anything they feel or experience on social media in the form of posts or comments. These posts, comments or reviews of the people can be analyzed using sentimental analysis, which is emerging field in text mining. COVID-19 has people's life all over the globe and thus has declared as pandemic. Due to COVID, people are feeling panic, anxiety, rage, sorrow, misery, stress and other issues. In this review, we have presented the sentimental analysis data sources, approaches, scenarios, methods and tools by comparing thirty studies. The results illustrated that most researchers have used SVM and Naive Bayes for sentimental analysis on COVID research. We also concluded that most of the researchers work on the sentiments of students, reopening sentiments, vaccine sentiments etc

    Energy and QoE aware Placement of Applications and Data at the Edge

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    Recent years are witnessing extensions of cyber-infrastructures towards distributed environments. The Edge of the network is gaining a central role in the agenda of both infrastructure and application providers. Following the actual distributed structure of such a computational environment, nowadays, many solutions face resource and application management needs in Cloud/Edge continua. One of the most challenging aspects is ensuring highly available computing and data infrastructures while optimizing the system's energy consumption. In this paper, we describe a decentralized solution that limits the energy consumption by the system without failing to match the users' expectations, defined as the services' Quality of Experience (QoE) when accessing data and leveraging applications at the Edge. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Data-driven, AI-based clinical practice: experiences, challenges, and research directions

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    Clinical practice is evolving rapidly, away from the traditional but inefficient detect-and-cure approach, and towards a Preventive, Predictive, Personalised and Participative (P4) vision that focuses on extending people’s wellness state. This vision is increasingly data-driven, AI-based, and is underpinned by many forms of "Big Health Data" including periodic clinical assessments and electronic health records, but also using new forms of self-assessment, such as mobile-based questionnaires and personal wearable devices. Over the last few years, we have been conducting a fruitful research collaboration with the Infectious Disease Clinic of the University Hospital of Modena having the main aim of exploring specific opportunities offered by data-driven AI-based approaches to support diagnosis, hospital organization and clinical research. Drawing from this experience, in this paper we provide an overview of the main research challenges that need to be addressed to design and implement data-driven healthcare applications. We present concrete instantiations of these challenges in three real-world use cases and summarise the specific solutions we devised to address them and, finally, we propose a research agenda that outlines the future of research in this field

    Like breadcrumbs in the forest

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    The recent explosion of freely available RDF datasets on the Web calls for new tools and techniques for semantic-enabled exploratory browsing. We present ENT, an HTML5-based tool that guides the user through the navigation of RDF graphs avoiding the visualization of information resulting irrelevant for the exploratory task. Thanks to a hypertree-based visualization of the data-space, the user has a clear picture both of his/her navigation path and of the information he/she may discove

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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