SemantrixA Compressed Semantic Matrix

  1. Nieves Rodríguez Brisaboa 1
  2. Antonio Fariña 1
  3. Gonzalo Navarro 2
  4. Tirso Varela Rodeiro 1
  1. 1 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

  2. 2 Universidad de Chile
    info

    Universidad de Chile

    Santiago de Chile, Chile

    ROR https://ror.org/047gc3g35

Libro:
Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021): [Málaga, 22 al 24 de septiembre de 2021]
  1. Rafael Capilla (coord.)
  2. Maider Azanza (coord.)
  3. Miguel Rodríguez Luaces (coord.)
  4. María del Mar Roldán García (coord.)
  5. Loli Burgueño (coord.)
  6. José Raúl Romero (coord.)
  7. José Antonio Parejo Maestre (coord.)
  8. José Francisco Chicano García (coord.)
  9. Marcela Genero (coord.)
  10. Oscar Díaz (coord.)
  11. José González Enríquez (coord.)
  12. Mª Carmen Penadés Gramaje (coord.)
  13. Silvia Abrahão (col.)

Editorial: Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (SISTEDES)

Año de publicación: 2021

Congreso: Jornadas de Ingeniería del Software y Bases de Datos (JISBD) (25. 2021. Malaga)

Tipo: Aportación congreso

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Resumen

We present a compact data structure to represent both the duration and length of homogeneous segments of trajectories from moving objects in a way that, as a data warehouse, it allows us to efficiently answer cumulative queries. The division of trajectories into relevant segments has been studied in the literature under the topic of Trajectory Segmentation. In this paper, we design a data structure to compactly represent them and the algorithms to answer the more relevant queries. We experimentally evaluate our proposal in the real context of an enterprise with mobile workers (truck drivers) where we aim at analyzing the time they spend in different activities. To test our proposal under higher stress conditions we generated a huge amount of synthetic realistic trajectories and evaluated our system with those data to have a good idea about its space needs and its efficiency when answering different types of queries.

Fuente de los datos: Dialnet