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Agrupamento tradicional e baseado em mapas para grandes conjuntos de dados: Uma Revisão Sistemática

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Description

Devido aos avanços digitais, grandes volumes de dados estão a ser gerados pelas aplicações modernas. A fim de categorizar com precisão os dados nestes grandes conjuntos de dados, são utilizados algoritmos de clustering. Este livro apresenta uma revisão bibliográfica de vários algoritmos tradicionais de agrupamento e as suas comparações a partir de uma perspectiva teórica. O livro fornece também o levantamento de aplicações de técnicas de agrupamento em I) dados de registo na web, II) dados de imagem e III) dados biológicos. Uma das maiores desvantagens dos algoritmos tradicionais de agregação é que são computacionalmente caros quando o tamanho dos dados de entrada é demasiado grande. Para ultrapassar este problema, fornecemos também um estudo abrangente dos recentes algoritmos de agregação baseados no MapReduce que alargam a contrapartida tradicional com o paradigma de programação Map-Reduce. Principalmente este livro é adequado para investigadores que estejam interessados no campo da descoberta de padrões a partir de grandes conjuntos de dados utilizando o agrupamento MapReduce. Ajudá-los-á a realizar a agregação de dados em ambiente distribuído. Mais importante ainda, as questões e áreas abertas discutidas neste livro ajudarão os investigadores a identificar a sua futura direcção.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
14 June 2022
Listed Since
15 June 2022

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