GI-LBD - Artigos
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Fed-mRMR: A lossless federated feature selection method
(Elsevier, 2024-05)[Abstract]: Feature selection has become a mandatory task in data mining, due to the overwhelming amount of features in Big Data problems. To handle this high-dimensional data and avoid the well-known curse of dimensionality, ... -
Local features: Enhancing variability modeling in software product lines
(Elsevier, 2024-07)[Abstract]: Context and motivation: Software Product Lines (SPL) enable the creation of software product families with shared core components using feature models to model variability. Choosing features from a feature model ... -
Scalable processing and autocovariance computation of big functional data
(John Wiley & Sons, 2018)[Abstract]: This paper presents 2 main contributions. The first is a compact representation of huge sets of functional data or trajectories of continuous-time stochastic processes, which allows keeping the data always ... -
GraCT: A Grammar-based Compressed Index for Trajectory Data
(Elsevier Ltd, 2019)[Abstract]: We introduce a compressed data structure for the storage of free trajectories of moving objects that efficiently supports various spatio-temporal queries. Our structure, dubbed GraCT, stores the absolute positions ... -
An index for moving objects with constant-time access to their compressed trajectories
(Taylor & Francis, 2021)[Abstract]: As the number of vehicles and devices equipped with GPS technology has grown explosively, an urgent need has arisen for time- and space-efficient data structures to represent their trajectories. The most commonly ...
