Listar Laboratorio de Bases de Datos (LBD) por título

Mostrando ítems 26-45 de 53

    • Fed-mRMR: A lossless federated feature selection method 

      Hermo González, Jorge; Bolón-Canedo, Verónica; Ladra, Susana (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, ...

    • From Coarse to Fine-Grained Parcellation of the Cortical Surface Using a Fiber-Bundle Atlas 

      López-López, Narciso; Vázquez, Andrea; Houenou, Josselin; Poupon, Cyril; Mangin, Jean-François; Ladra, Susana; Guevara, Pamela (Frontiers Research Foundation, 2020-09-10)
      [Abstract] In this article, we present a hybrid method to create fine-grained parcellations of the cortical surface, from a coarse-grained parcellation according to an anatomical atlas, based on cortico-cortical connectivity. ...

    • GraCT: A Grammar Based Compressed Representation of Trajectories 

      Brisaboa, Nieves R.; Gómez-Brandón, Adrián; Navarro, Gonzalo; Paramá, José R. (Springer, 2016-09-21)
      [Abstract] We present a compressed data structure to store free trajectories of moving objects (ships over the sea, for example) allowing spatio-temporal queries. Our method, GraCT, uses a k2k2 -tree to store the absolute ...

    • 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 ...

    • Grammar compressed sequences with rank/select support 

      Ordóñez, Alberto; Navarro, Gonzalo; Brisaboa, Nieves R. (Elsevier BV, 2016-10-14)
      [Abstract] Sequence representations supporting not only direct access to their symbols, but also rank/select operations, are a fundamental building block in many compressed data structures. Several recent applications need ...

    • Graph Compression for Adjacency-Matrix Multiplication 

      Francisco, Alexandre P.; Gagie, Travis; Köppl, Dominik; Ladra, Susana; Navarro, Gonzalo (Springer, 2022)
      [Abstract] Computing the product of the (binary) adjacency matrix of a large graph with a real-valued vector is an important operation that lies at the heart of various graph analysis tasks, such as computing PageRank. In ...

    • Improved Compressed String Dictionaries 

      Brisaboa, Nieves R.; Cerdeira-Pena, Ana; Bernardo, Guillermo de; Navarro, Gonzalo (ACM, 2019-11-03)
      [Abstract] We introduce a new family of compressed data structures to efficiently store and query large string dictionaries in main memory. Our main technique is a combination of hierarchical Front-coding with ideas from ...

    • Local features: Enhancing variability modeling in software product lines 

      Castro, David de; Cortiñas, Alejandro; Rodríguez Luaces, Miguel; Pedreira, Óscar; Saavedra Places, Ángeles (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 ...

    • 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 ...

    • Managing Compressed Structured Text 

      Brisaboa, Nieves R.; Cerdeira-Pena, Ana; Navarro, Gonzalo (Springer Nature, 2018-12-07)
      [Definition]: Compressing structured text is the problem of creating a reduced-space representation from which the original data can be re-created exactly. Compared to plain text compression, the goal is to take advantage ...

    • 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, ...

    • Modeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spain 

      Vallejo, J. A.; Trigo Tasende, Noelia; Rumbo-Feal, Soraya; Conde-Pérez, Kelly; López-Oriona, Ángel; Barbeito, Inés; Vaamonde, Manuel; Tarrío-Saavedra, Javier; Reif López, Rubén; Ladra, Susana; Rodiño-Janeiro, Bruno Kotska; Nasser-Ali, Mohammed; Cid, Ángeles; Veiga, María Carmen; Acevedo, Antón; Lamora, Carlos; Bou, Germán; Cao, Ricardo; Poza, Margarita (Elsevier, 2022)
      [Abstract] The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID–19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW ...

    • Multilevel Modeling of Geographic Information Systems Based on International Standards 

      Alvarado, Suilen H.; Cortiñas, Alejandro; Rodríguez Luaces, Miguel; Pedreira, Óscar; Saavedra Places, Ángeles (SpringerLink, 2021)
      [Abstract] Even though different applications based on Geographic Information Systems (GIS) provide different features and functions, they all share a set of common concepts (e.g., spatial data types, operations, services), ...

    • Navigational Rule Derivation: An algorithm to determine the effect of traffic signs on road networks 

      Galaktionov, Daniil; Rodríguez Luaces, Miguel; Saavedra Places, Ángeles (2016-11-17)
      [Abstract] In this paper we present an algorithm to build a road network map enriched with traffic rules such as one-way streets and forbidden turns, based on the interpretation of already detected and classified traffic ...

    • New machine learning approaches for real-life human activity recognition using smartphone sensor-based data 

      García-González, Daniel; Rivero, Daniel; Fernández-Blanco, Enrique; Rodríguez Luaces, Miguel (Elsevier B.V., 2023)
      [Abstract]: In recent years, mainly due to the application of smartphones in this area, research in human activity recognition (HAR) has shown a continuous and steady growth. Thanks to its wide range of sensors, its size, ...

    • Optimization in Sanger sequencing 

      Carpente, Luisa; Cerdeira-Pena, Ana; Lorenzo Freire, Silvia; Saavedra Places, Ángeles (Elsevier, 2019-09)
      [Abstract]: The main objective of this paper is to solve the optimization problem that is associated with the classification of DNA samples in PCR plates for Sanger sequencing. To achieve this goal, we design an integer ...

    • Parallel construction of wavelet trees on multicore architectures 

      Fuentes Sepúlveda, José; Elejalde, Erick; Ferres, Leo; Seco, Diego (Springer U K, 2016-10-05)
      [Abstract] The wavelet tree has become a very useful data structure to efficiently represent and query large volumes of data in many different domains, from bioinformatics to geographic information systems. One problem ...

    • Revisiting Compact RDF Stores Based on k2-Trees 

      Brisaboa, Nieves R.; Cerdeira-Pena, Ana; Bernardo, Guillermo de; Fariña, Antonio (IEEE Xplore, 2020-03)
      [Abstract]: We present a new compact representation to efficiently store and query large RDF datasets in main memory. Our proposal, called BMatrix, is based on the k 2 -tree, a data structure devised to represent binary ...

    • 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 ...