Laboratorio de Bases de Datos (LBD)
Envíos recentes
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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 ... -
Augmented Thresholds for MONI
(Institute of Electrical and Electronics Engineers Inc., 2023)[Abstract]: MONI (Rossi et al., 2022) can store a pangenomic dataset T in small space and later, given a pattern P, quickly find the maximal exact matches (MEMs) of P with respect to T. In this paper we consider its one-pass ... -
3DGraCT: A Grammar-Based Compressed Representation of 3D Trajectories
(Springer, 2018)[Abstract]: Much research has been published about trajectory management on the ground or at the sea, but compression or indexing of flight trajectories have usually been less explored. However, air traffic management is ... -
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 ...
