2 resultados para Closed caption

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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The problem of the relevance and the usefulness of extracted association rules is of primary importance because, in the majority of cases, real-life databases lead to several thousands association rules with high confidence and among which are many redundancies. Using the closure of the Galois connection, we define two new bases for association rules which union is a generating set for all valid association rules with support and confidence. These bases are characterized using frequent closed itemsets and their generators; they consist of the non-redundant exact and approximate association rules having minimal antecedents and maximal consequences, i.e. the most relevant association rules. Algorithms for extracting these bases are presented and results of experiments carried out on real-life databases show that the proposed bases are useful, and that their generation is not time consuming.

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Comparing the experiences of selected Latin America and the Caribbean countries and their trajectories over the past 15 years offers rich insights into the dynamics and causes for not meeting the 2015 MDGs. They also offer clues for post-MDG strategies. Central to achieving sustainable growth are government policies able to support small and medium-sized farms and peasants, as they are crucial for the achievement of several goals, centrally: to achieve food security; to provide a sound and stable rural environment able to resist external (financial) shocks; to secure healthy food; to secure local food; and to protect vibrant and culturally rich local communities. This paper analyses and compares the most successful government policies to the least successful policies carried out over the last 15 years in selected Latin American and Caribbean countries and based on this analysis, offers strategies for more promising post-MDG politics, able to reduce poverty, reduce inequality, fight back informality, and achieve more decent work in poor countries.