8 resultados para Library information networks

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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In this paper we have quantified the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood. Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for eight authors indicated that these indices may be employed for author recognition. Indeed, as expected, authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other tasks, such as emotion recognition.

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Este artigo procura construir um panorama não extensivo do tema cibercultura. Passa pela conceituação de cibercultura mais utilizada; recupera a correlação. ciber/contra/cultura; correlaciona a cena cibercultural às possibilidades de criação e disseminação da cultura, da informação e do conhecimento em geral por meio das redes informacionais; e discute o seu papel na construção das competências comunicativas na sociedade contemporânea

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Este trabalho relata a experiência e os procedimentos adotados em um processo de análise e identificação dos títulos de periódicos recebidos pela Biblioteca do Instituto de Medicina Tropical de São Paulo da Universidade de São Paulo, desde sua criação. Para a coleta de dados foram utilizadas as informações dos registros bibliográficos no Módulo de Catalogação no Banco de Dados Bibliográficos – DEDALUS Aleph 500 Versão 18.1 da Universidade de São Paulo, seguindo alguns critérios pré-estabelecidos. Conclui-se que, apesar dos problemas detectados serem pouco relevantes em relação ao acervo analisado, deve-se manter um estudo comparativo entre a necessidade do usuário e a coleção disponível na Biblioteca, para que os periódicos atendam às necessidades de informação de seus usuários.

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PO artigo demonstra as interações entre algumas bases de dados internacionais na disponibilização de periódicos da área de Ciência da Informação. Para isso, foram investigadas seis bases de dados com acesso a texto completo dentro da área de Ciência da Informação. Foram elas: Web of Science, Scopus, Library, Information Science & Technology Abstracts, Information Science & Technology Abstracts, Library Literature Information Science – full text e Library Information Science Abstract. No desenvolvimento da pesquisa foram utilizados conceitos, princípios e equações da ‘teoria ingênua dos conjuntos’, o que permitiu observar as bases de dados como conjuntos compostos por elementos, aqui considerados os títulos de periódicos, bem como conferir consistência aos resultados. A análise dos dados foi dividida em três etapas, a saber: a) a primeira priorizou o cruzamento entre as duas maiores bases de dados utilizadas para levantamento bibliográfico (Web of Science e Scopus), seguido do cruzamento com a mais utilizada na Ciência da Informação, a Library and Information Science Abstracts; b) a segunda etapa tratou somente do cruzamento das bases especialistas da área; c) a terceira e última etapa tratou da interseção de todas as bases de dados do estudo. O resultado mostra que 10 títulos de periódicos constituem a interseção dos seis conjuntos de bases de dados. Foi possível identificar, também, o número de periódicos disponibilizados exclusivamente por uma base de dados, demonstrando que as necessidades de pesquisas bibliográficas exaustivas passam, obrigatoriamente, pelo levantamento em todas as bases de dados aqui elencadas.

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The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators.

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This work clarifies the relationship between network circuit (topology) and behavior (information transmission and synchronization) in active networks, e. g. neural networks. As an application, we show how to determine a network topology that is optimal for information transmission. By optimal, we mean that the network is able to transmit a large amount of information, it possesses a large number of communication channels, and it is robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

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The number of citations received by authors in scientific journals has become a major parameter to assess individual researchers and the journals themselves through the impact factor. A fair assessment therefore requires that the criteria for selecting references in a given manuscript should be unbiased with regard to the authors or journals cited. In this paper, we assess approaches for citations considering two recommendations for authors to follow while preparing a manuscript: (i) consider similarity of contents with the topics investigated, lest related work should be reproduced or ignored; (ii) perform a systematic search over the network of citations including seminal or very related papers. We use formalisms of complex networks for two datasets of papers from the arXiv and the Web of Science repositories to show that neither of these two criteria is fulfilled in practice. By representing the texts as complex networks we estimated a similarity index between pieces of texts and found that the list of references did not contain the most similar papers in the dataset. This was quantified by calculating a consistency index, whose maximum value is one if the references in a given paper are the most similar in the dataset. For the areas of "complex networks" and "graphenes", the consistency index was only 0.11-0.23 and 0.10-0.25, respectively. To simulate a systematic search in the citation network, we employed a traditional random walk search (i.e. diffusion) and a random walk whose probabilities of transition are proportional to the number of the ingoing edges of the neighbours. The frequency of visits to the nodes (papers) in the network had a very small correlation with either the actual list of references in the papers or with the number of downloads from the arXiv repository. Therefore, apparently the authors and users of the repository did not follow the criterion related to a systematic search over the network of citations. Based on these results, we propose an approach that we believe is fairer for evaluating and complementing citations of a given author, effectively leading to a virtual scientometry.

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Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.