Listar GI-LBD - Artigos por autor "Paramá, José R."

Mostrando ítems 1-8 de 8

    • An index for moving objects with constant-time access to their compressed trajectories 

      Brisaboa, Nieves R.; Gagie, Travis; Gómez-Brandón, Adrián; Navarro, Gonzalo; Paramá, José R. (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 ...

    • Compact and indexed representation for LiDAR point clouds 

      Ladra, Susana; Rodríguez Luaces, Miguel; Paramá, José R.; Silva-Coira, Fernando (Taylor & Francis, 2022)
      [Abstract]: LiDAR devices are capable of acquiring clouds of 3D points reflecting any object around them, and adding additional attributes to each point such as color, position, time, etc. LiDAR datasets are usually large, ...

    • Efficient Processing of Raster and Vector Data 

      Silva-Coira, Fernando; Paramá, José R.; Ladra, Susana; López, Juan R.; Gutiérrez, Gilberto (Public Library of Science, 2020-01-10)
      [Abstract] In this work, we propose a framework to store and manage spatial data, which includes new efficient algorithms to perform operations accepting as input a raster dataset and a vector dataset. More concretely, we ...

    • GraCT: A Grammar-based Compressed Index for Trajectory Data 

      Brisaboa, Nieves R.; Gómez-Brandón, Adrián; Navarro, Gonzalo; Paramá, José R. (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 ...

    • Lossless Compression of Industrial Time Series With Direct Access 

      Gómez-Brandón, Adrián; Paramá, José R.; Villalobos, Kevin; Illarramendi, Arantza; Brisaboa, Nieves R. (Elsevier, 2021)
      [Abstract] The new opportunities generated by the data-driven economy in the manufacturing industry have causedmany companies opt for it. However, the size of time series data that need to be captured creates theproblem ...

    • Map algebra on raster datasets represented by compact data structures 

      Silva-Coira, Fernando; Paramá, José R.; Ladra, Susana (John Wiley and Sons, 2023-06)
      [Abstract]: The increase in the size of data repositories has forced the design of new computing paradigms to be able to process large volumes of data in a reasonable amount of time. One of them is in-memory computing, ...

    • Scalable processing and autocovariance computation of big functional data 

      Brisaboa, Nieves R.; Cao, Ricardo; Paramá, José R.; Silva-Coira, Fernando (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 ...

    • Space-Efficient Representations of Raster Time Series 

      Silva-Coira, Fernando; Paramá, José R.; Bernardo, Guillermo de; Seco, Diego (Elsevier, 2021)
      [Abstract] Raster time series, a.k.a. temporal rasters, are collections of rasters covering the same region at consecutive timestamps. These data have been used in many different applications ranging from weather forecast ...