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Tarefas de mineração e analise de dados de trajetórias têm sido amplamente estudadas nos últimos anos. Essas tarefas são complexas devido ao grande volume de dados gerados e sua heterogeneidade. Uma solução para minimizar esses problemas é a sumarização desses dados, visando gerar dados representativos. Poucos trabalhos na literatura se direcionam a estas soluções, e não foi encontrada nenhuma que considere todas as dimensões de uma trajetória (espacial, temporal e ilimitados aspectos semânticos), analisando as peculiaridades e singularidades de cada aspecto. Essa tese de doutorado propõe um método baseado em uma grade espacial para sumarização de trajetórias de múltiplos aspectos, chamado MAT-SG. Suas principais contribuições são: (i) segmentação das trajetórias em uma grade espacial de acordo com a dispersão dos pontos; (ii) a partir de um conjunto de trajetórias de entrada, uma trajetória representativa é gerada como uma sequência de pontos representativos com valores representativos para cada dimensão, considerando as particularidades de cada tipo de aspecto. Um exemplo demonstra o potencial da proposta, sendo avaliadas a redução de volume e a acurácia da sumarização.

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Trajectory data mining and analysis tasks have been widely studied in recent years. These tasks are complex due to the large volume of data generated and its heterogeneity. A solution to minimize these problems is the summarization of these data, aiming to generate representative data. Few works in the literature address these solutions, and none were found that consider all dimensions of a trajectory (spatial, temporal and unlimited semantic aspects), analyzing the peculiarities and singularities of each aspect. This doctoral thesis proposes a method based on a spatial grid for summarizing multi-aspect trajectories, called MAT-SG. Its main contributions are: (i) segmentation of trajectories in a spatial grid according to the dispersion of points; (ii) from a set of input trajectories, a representative trajectory is generated as a sequence of representative points with representative values for each dimension, considering the particularities of each type of aspect. An example demonstrates the potential of the proposal, being evaluated the volume reduction and the accuracy of the summarization.

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#	Name
1	Vanessa Machado(vanessalagomachado@gmail.com)
2	Ronaldo Mello(r.mello@ufsc.br)
3	Vânia Bogorny(vania.bogorny@ufsc.br)

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