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Multiplayer Online Battle Arena (MOBA) games are very popular in the current eSport scenario, being highlighted in several competitions around the world. However, the domain of knowledge contained in these games is large, which makes it difficult to discover and predict the course of a match. The present work proposes the application of classification algorithms to determine the team with more chances...
Social networks are of significant analytical interest. This is because their data are generated in great quantity, and intermittently, besides that, the data are from a wide variety, and it is widely available to users. Through such data, it is desired to extract knowledge or information that can be used in decision-making activities. In this context, we have identified the lack of methods that apply...
The process of Knowledge Discovery in Databases, or KDD for short, have been intensively used in tasks focused on searching useful information based on data. The reason is that such data is generated in significant volume, high speed and with a large variety, which makes it require accurate, efficient and scalable methods to handle them. Due to this scenario, several tools and methodologies have been...
The volume of data exchanged by computer networks is gradually increasing over time, which provides the need for performance and interoperability between different platforms and systems. In this line, there are several studies dedicated to service-oriented software architectures and resource consumption models. However, a few of them are focused on the development of generic tools for the dynamic...
The wide availability of database systems and low cost of hardware allow enterprises and researchers the opportunity to store large data collections. The challenge then became the understanding of these data. To overcome this problem Information Visualization (IV) techniques have been employed to amplify the human cognitive ability through graphical data representations, that show properties and relationships...
Fiber tracts detection is an increasingly common technology for diagnosis and also understanding of brain function. Although tools for tracing and presenting brain fibers are advanced, it is still difficult for physicians or students to explore the dataset in 3D due to their intricate topology. In this work we present a visual exploration approach for fiber tracts data aimed at supporting exploration...
Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image—Projection Explorer for Images—a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus...
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