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    Two essays on high-dimensional classification and clustering analysis

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    High-dimensionality is one of the most challenging problems that has arisen in the past decade. Although data mining technology has been greatly developed, new challenges still emerge with respect to specific data structures. In order to discover previously unknown patterns and make predictions, we have to overcome these challenges. Moreover, when interactions among explanatory variables are taken into account, the dimensionality becomes even larger. Thus, feature selection is a hot topic in terms of supervised and unsupervised learning. In Essay 1 of this dissertation, we consider the business data mining problem, using the Amazon employee’s access as an example, to demonstrate the proposed feature selection and classification methods. First, when we apply Naive Bayes classifiers to the data set, the classifiers are modified step-by-step with ideas of Empirical Bayes, grouping, and migration. Second, we propose a three-stage Bayesian hierarchical model with regards to the special data structure. Also, because of the categorical structure, we propose a method for variable selection: Coefficient of Dependence (CoD). Finally, ensemble learning is used to bring together the classifiers as a whole. When carrying out the procedure, a technique that we refer to as Stringing is applied. The newly-developed classifiers outperform most of the existing models in terms of the ranking of the competition. Essay 2 contains a clustering analysis model, referred to as Beta-binomial mixture model. This idea comes from the classic Gaussian Mixture Model (GMM), as a method of distribution-based clustering. In distribution-based clustering, objects are clustered based on their similarities to the same distribution. An Expectation-maximization (EM) algorithm is used to fulfill the unsupervised model.</p

    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

    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

    Strong Consistency of Bayes Estimates in Stochastic Regression Models

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    Under minimum assumptions on the stochastic regressors, strong consistency of Bayes estimates is established in stochastic regression models in two cases: (1) When the prior distribution is discrete, the p.d.f.fof i.i.d. random errors is assumed to have finite Fisher informationI=[integral operator][infinity]-[infinity](f')2/f dxBayes estimates stochastic regressor martingale system identification adaptive control dynamic model strongly unimodal

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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