April 2025
Intermediate to advanced
268 pages
6h 17m
Portuguese (Portugal, Brazil)
Content preview from Algoritmos de grafos
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Capítulo 5. Algoritmos de centralidade
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Os algoritmos de centralidade são utilizados para compreender os papéis de determinados nós num gráfico e o seu impacto nessa rede. São úteis porque identificam os nós mais importantes e ajudam-nos a compreender a dinâmica de grupo, como a credibilidade, a acessibilidade, a velocidade a que as coisas se espalham e as pontes entre grupos. Embora muitos destes algoritmos tenham sido inventados para a análise de redes sociais, desde então têm sido utilizados numa variedade de indústrias e domínios.
Abordaremos os seguintes algoritmos:
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Centralidade de grau como uma métrica de base de conetividade
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Closeness Centrality para medir a centralidade de um nó no grupo, incluindo duas variações para grupos desconectados
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Betweenness Centrality para encontrar pontos de controlo, incluindo uma alternativa para aproximação
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PageRank para compreender a influência global, incluindo uma opção popular para personalização
Dica
Diferentes algoritmos de centralidade podem produzir resultados significativamente diferentes com base no que foram criados para medir. Quando vês respostas abaixo do ideal, é melhor verificar se o algoritmo que utilizaste está alinhado com o objetivo pretendido.
Explicaremos como estes algoritmos funcionam e mostraremos exemplos no Spark e no Neo4j. Quando um algoritmo não estiver disponível numa plataforma ou ...
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